• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1475-1482
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• 2010

This paper aims at finding the policy implications of mobile government services based on the comparison of domestic and foreign cases. We developed a framework for the classification of mobile government services and examined the domestic and foreign mobile government services to identify policy implications and dynamic trends of the mobile government. In the policy perspective, we suggest customer-centric service redesign, extensive adoption of mobile service solutions, and new service development reflecting new mobile trends.

• Industrial Engineering and Management Systems
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• v.10 no.4
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• pp.272-278
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• 2011

Decision tree as a classification tool is being used successfully in many areas such as medical diagnosis, customer churn prediction, signal detection and so on. The main advantage of decision tree classifiers is their capability to break down a complex structure into a collection of simpler structures, thus providing a solution that is easy to interpret. Since decision tree is a top-down algorithm using a divide and conquer induction process, there is a risk of reaching a local optimal solution. This paper proposes a procedure of optimally determining thresholds of the chosen variables for a decision tree using an adaptive particle swarm optimization (APSO). The proposed algorithm consists of two phases. First, we construct a decision tree and choose the relevant variables. Second, we find the optimum thresholds simultaneously using an APSO for those selected variables. To validate the proposed algorithm, several artificial and real datasets are used. We compare our results with the original CART results and show that the proposed algorithm is promising for improving prediction accuracy.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.440-443
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• 2005

The wide spread of internet business recently necessitates recommendation systems which can recommend the most suitable product fur customer demands. Currently the recommendation systems use content-based filtering and/or collaborative filtering methods, which are unable both to explain the reason for the recommendation and to reflect constantly changing requirements of the users. These methods guarantee good efficiency only if there is a lot of information about users. This paper proposes an algorithm called 'demand articulate & integration' which can perceive user's continuously varying intents and recommend proper contents. A method of knowledge classification which can be applicable to this algorithm is also developed in order to disassemble knowledge into basic units and articulate indices. The algorithm provides recommendation outputs that are close to expert's opinion through the tracing of articulate index. As a case study, a knowledge base for heritage information is constructed with the expert guide's knowledge. An intelligent recommendation system that can guide heritage tour as good as the expert guider is developed.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.5 s.164
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• pp.765-776
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• 2007

Customer expectations and requirements for products play an important role in product planning for companies and decision making process for the consumer. These expectations are expressed by product qualities that consumers consider important when they purchase. Therefore, to identify quality elements that reflect consumer requirements would be a useful guide for companies. The purposes of this study are to find out quality factors of apparel product, to identify apparel product quality elements using Kano's theory, to find attributes of product which improvement are required. Women over 20 years-old from metropolitan areas in South Korea participated in the study and a quota sampling method was used. A questionnaire was arranged with four separate subject sections, importance of quality, Kano's questionnaires, and demographics. Data from 525 questionnaires were used for the statistical analysis. The results were as follows: Six dimensions of product quality(i.e., usefulness, performance, aesthetic, symbol, individuality and appearance) were identified. According to Kano's quality elements, performance was categorized into must-be quality which could lead to product dissatisfaction. Usefulness and appearance were categorized into one-dimensional quality which lead to both satisfaction and dissatisfaction. Aesthetic, symbol, and individuality was categorized into attractive quality which could lead to satisfaction. Findings of this study provide both industry and academic researchers with a guide to increase customer satisfaction in the product development process.

• Journal of the East Asian Society of Dietary Life
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• v.20 no.3
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• pp.389-395
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• 2010

This research was focused on observing the effect of Makgeolli's selection attributes on customer satisfaction, recommendation intention, and repurchase intention. The purpose of this study was to examine to present a marketing-related suggestion by finding the components that needs to be discussed in order to satisfy the customer and lead to positive word of mouth and repurchasing in the perspective of a corporation. The evidence to achieve the research purpose can be summarized as below. To begin with, the causes of Makgeolli's selection attributes were classified into 9 types, which are design and ad image, expertise and tradition, drinking experience and in harmony with food, taste and freshness, materials and origin, brand image, flavor and color, alcoholic and nutrition, and finally price and recommendation. And it showed up that the average importance of the taste and freshness is the highest. Moreover, the study on the Makgeolli's state of being potable showed up that the drinking number was no more than once a month, and one drink was almost all less than a bottle. The drinking place was usually tavern, and word of mouth was the most often used information medium that contacted Makgeolli. The potential of the Makgeolli's globalization is 80.6% which added positive and very positive, that enables us to infer that the Makgeolli's global dependency is very high. Third, from the 9 types of classification mentioned before, taste and freshness, and price and recommendation were proved to be influential in satisfaction, and recommendation is affecting the repurchase intention and the recommendation intention.

• The Journal of Industrial Distribution & Business
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• v.10 no.7
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• pp.71-82
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• 2019

Purpose - This study aims to identify the priorities of medical service quality improvement by customer satisfaction characteristics and potential customer satisfaction improvement (PCSI) index based on the dualistic quality classification of Kano Model (1984) for Comprehensive Health Screeening Center in General Hospitals and Centers only for Comprehensive Health Screening and suggest a direction for future improvement. Research design, data, and methodology - Through advanced research on health screening medical service quality, this study set four service quality factors, including tangible, human, process and supportive factors, and 39 measurement items. Based on these items, the study used 117 questions, which consist of dualistic quality factors, customer satisfaction coefficients, positive and negative questions for PCSI index and questions for current satisfaction. 300 effective samples were collected for adults in their 20s who experienced health screening service in Seoul, Gyeonggi-do and Incheon within the past two years. Collected data were input in the quality evaluation duality table to categorize quality factors and calculate customer satisfaction coefficients by Timko(1993). The study also analyzed PCSI index in comparison with current satisfaction and identified priorities in quality improvement. Results - It was found that the most urgent factors to improve the quality in both groups were adequate waiting hours and emergency response for complications, which are process factors classified as unitary quality. It is urgently needed to improve the quality as the PCSI index was high in supportive factors (complaint response team) as attractive quality in Comprehensive Health Screening Center in General Hospitals and in process factors (prevention of infection) as unitary quality in Centers only for Comprehensive Health Screening. As the PCSI index was low in space use as a tangible factor, it was found that the current level can be maintained instead of improvement. Conclusions - To improve the health screening medical service quality, it is required to focus on process factors (adequate waiting hours, emergency response for complications, prevention of infection) and supportive factors (complaint response team) among service qualities perceived by users. It is proposed to ensure continuous efforts to manage and reinforce priorities as a direction for future improvement in health screening service.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• Korean Journal of Construction Engineering and Management
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• v.9 no.1
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• pp.126-133
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• 2008

Current changing to the customer-oriented market naturally causes suppliers to meet an age of competition on the quality. In order to plan housing meeting this quality competitiveness era, I set up the type classification system of quality differentiation for the unit of apartment housing by executing differentiation cases of unit quality and type analysis of the object. The system is consist of 3 classification systems by quality element, user convenience element and product element as follows: First element is to classify quality element on the basis of plane and interior elements, architectural elements and second one is user convenience element relating facility to classify environment-oriented, safety, energy saving and convenience. The other one is the product element to classify furniture, installing product and convenient product. I believe that this classification system will be useful to determine any classification elements of product for product positioning and product planning in the stage of marketing planning of apartment housing in the future.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.333-336
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• 2001

The future industry, intangible assets, like expertise, customer satisfaction, and employee's volition and capability, create more company value than any other components. The company's outcome mostly depends on managing these intangible knowledge assets. Construction industry is trying to adapt knowledge management system to manage their knowledge assets, but Hey do not build up knowledge assets definition and knowledge assets classification as much as other industries do. Most researches related knowledge assets classification are not concentrated on construction industry so it is need to define knowledge assets and establish knowledge assets classification of construction based on construction characteristics and informations. With this research result, construction knowledge assets classification can be the basis of knowledge asscts evaluation and knowledge map for knowledge management system.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.17-25
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• 2001

Tree model is the most popular classification algorithm in data mining due to easy interpretation of the result. In CART(Breiman et al., 1984) and C4.5(Quinlan, 1993) which are representative of tree algorithms, the split fur classification proceeds to attain the homogeneous terminal nodes with respect to the composition of levels in target variable. But, fur instance, in the chum prediction modeling fur CRM(Customer Relationship management), the rate of churn is generally very low although we are interested in mining the churners. Thus it is difficult to get accurate prediction modes using tree model based on the traditional split rule, such as mini or deviance. Buja and Lee(1999) introduced a new split rule, one-sided purity for classifying minor interesting group. In this paper, we compared one-sided purity with traditional split rule, deviance analyzing churning vs. non-churning data of ISP company. Also reviewing the result of tree model based on one-sided purity with some simulated data, we discussed problems and researchable topics.