• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3B
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• pp.175-182
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• 2007

In recent years, there have been active researches on the services of the next generation mobile communications. In particular, the services in the next generation mobile communications differ from the services in the conventional mobile communication services that they can provide the services customized at each user. The profile management technology becomes more important for such personalized services since it is closely related with providing services adaptively to user's current situation and preferences. However, the conventional profile management technologies have their limitations on providing personalized services because they put most of emphasis on the customer management. Even, it becomes more difficult with current profile management system to support the personalized services, where the service providers manage the user profiles independently each other. In this paper, we propose a novel profile management system called profile service provider, and describe the requirements to support personalized services in the next generation mobile communications.

• International Journal of Quality Innovation
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• v.9 no.3
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• pp.71-91
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• 2008

The definition of cycle time is the time from the wafer start to the wafer output. It usually takes one or two months to get the product since customer decides to produce it. The cycle time is a critical factor for customer satisfaction because it represents the response time to the market. Long cycle time reflects the ineffective investment for the capital. The cycle time is very important for foundry because long cycle time will cause customer unsatisfied and the order loss. Consequently, all of the foundries put lots of human source in the cycle time improvement. Usually, we make decisions based on the experience in the cycle time management. We have no mechanism or theory for cycle time management. We do work-in-process (WIP) management based on turn rate and standard WIP (STD WIP) set by experiences. But the experience didn't mean the optimal solution, when the situation changed, the cycle time or the standard WIP will also be changed. The experience will not always be applicable. If we only have the experience and no mechanism, management will not be work out. After interview several foundry fab managers, all of the fab can't reflect the situation. That is, all of them will have an impact period after product mix or utilization varied. In this study, we want to develop a formula for standard WIP and use statistical process control (SPC) concept to set WIP upper/lower limit level. When WIP exceed the limit level, it will trigger action plans to compensate WIP Profile. If WIP Profile balances, we don't need too much WIP. So WIP level could be reduced and cycle time also could be reduced.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.67-74
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• 2011

Collaborative recommendation is one of the most widely used methods of automated product recommendation in e-Commerce. For analyzing the customer's preference, traditional explicit ratings are less desirable than implicit ratings because it may impose an additional burden to the customers of e-commerce companies which deals with a number of products. Cardinal scales generally used for representing the preference intensity also ineffective owing to its increasing estimation errors. In this paper, we propose a new way of constructing the ordinal scale-based customer profile for collaborative recommendation. A Web usage mining technique and lexicographic consensus are employed. An experiment shows that the proposed method performs better than existing CF methodologies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4626-4631
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• 2011

In this paper, we design an ubiquitous-type shopping mall using RFID(Radio Frequency IDentification) technology and a location analysis system which can locate customers in real time at off-line shopping malls as a way to provide any services to customers, based on the results of environmental analysis data. We also suggest an intelligent agent system which can provide a personalized information in time.

• Journal of Information Technology Applications and Management
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• v.14 no.4
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• pp.221-233
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• 2007

Which factors should influence consumer consideration to subscribe to Voice over Internet Protocol (VoIP)? Policy issues, managerial concerns, and demographic variables are possible factors. This paper discusses policy and managerial issues regarding VoIP adoption. A model that explains VoIP adoption is proposed and tested. This study analyzes a survey of 750 prospective VoIP users in Korea. The testing is accompanied by logistic regression and discriminant analysis. The results show that trust in VoIP, relative comparison of Quality to fixed service, numbering plan, satisfactions of call Quality and customer services on both fixed and mobile services have impacts on the adoption of VoIP. Implications for VoIP providers and policy makers are presented.

• Asia pacific journal of information systems
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• v.9 no.4
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• pp.107-124
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• 1999

This paper describes a personalized advertisement technique as a part of intelligent customer services in Internet shopping malls. Based on customers' initial profile, purchase history, and behaviors in an Internet shopping mall, the technique displays appropriate advertisements on Internet web pages when customers' visit to the shopping mall. Customers preference scores for product groups which are main sources to select advertisements, are stored either a preference table or preference trees. Both of the two storage methods can support selection of advertisements on real time, and the preference tree method can reflect affinity among product groups. The suggested technique selects different advertisements to reflect changes of customers preferences as time goes by. An experiment has been performed to evaluate the effectiveness of the algorithm, which revealed that the algorithm selects more customer-oriented advertisements rather than random selection.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.39-56
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• 2012

Technological advancements in information technology including RFID and mobile technologies have made it feasible to track the customers travel path in a store. The customer travel paths provide valuable implications to understanding the customer behaviors in a store. In our research, we develop a shopping path analysis system to track and analyze the customer travel path. The proposed system consists of RFID systems for collecting the customer paths and analysis system. The analysis system conducts clustering for identifying the distinctive shopping patterns, and analyzes the profile of a grocery, such as congestion rate, visiting rate, and staying time, etc. We show the applicability of our proposed system using the actual data obtained at a grocery in Seoul as a case study.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.4
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• pp.571-582
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• 2000

The purposes of this study were to segment department store customers based on patronage orientations of service facilities in a department store and to develop a profile of each segment using store visit behaviors, clothing purchase behaviors and demographics. A total of 453 responses collected from an on-site questionnaire survey to female department store customers was analyzed. Cluster analysis on patronage orientations of department store service facilities identified four groups including: Active patrons(27.3%); Comparison patrons(27.6%); Convenience seekers(27.3%); and Minimum patrons(17.8%). ANOVA and $\chi$$^2$ analyses revealed significant differences among the four groups on store visit behaviors(the extent of store visits and the extent of service facility visits), clothing purchase behaviors(6 store choice criteria and the extent of clothing purchase), and 5 demographic characteristics. The study developed a profile of each segment and provided marketing implications.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.61-75
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• 2011

A Geographic Information System(GIS) is a system that captures, stores, analyzes, manages and presents data with reference to geographic location data. In the later 1990s and earlier 2000s it was limitedly used in government sectors such as public utility management, urban planning, landscape architecture, and environmental contamination control. However, a growing number of open-source packages running on a range of operating systems enabled many private enterprises to explore the concept of viewing GIS-based sales and customer data over their own computer monitors. K telecommunication company has dominated the Korean telecommunication market by providing diverse services, such as high-speed internet, PSTN(Public Switched Telephone Network), VOLP (Voice Over Internet Protocol), and IPTV(Internet Protocol Television). Even though the telecommunication market in Korea is huge, the competition between major services providers is growing more fierce than ever before. Service providers struggled to acquire as many new customers as possible, attempted to cross sell more products to their regular customers, and made more efforts on retaining the best customers by offering unprecedented benefits. Most service providers including K telecommunication company tried to adopt the concept of customer relationship management(CRM), and analyze customer's demographic and transactional data statistically in order to understand their customer's behavior. However, managing customer information has still remained at the basic level, and the quality and the quantity of customer data were not enough not only to understand the customers but also to design a strategy for marketing and sales. For example, the currently used 3,074 legal regional divisions, which are originally defined by the government, were too broad to calculate sub-regional customer's service subscription and cancellation ratio. Additional external data such as house size, house price, and household demographics are also needed to measure sales potential. Furthermore, making tables and reports were time consuming and they were insufficient to make a clear judgment about the market situation. In 2009, this company needed a dramatic shift in the way marketing and sales activities, and finally developed a dedicated GIS_based market analysis and sales management system. This system made huge improvement in the efficiency with which the company was able to manage and organize all customer and sales related information, and access to those information easily and visually. After the GIS information system was developed, and applied to marketing and sales activities at the corporate level, the company was reported to increase sales and market share substantially. This was due to the fact that by analyzing past market and sales initiatives, creating sales potential, and targeting key markets, the system could make suggestions and enable the company to focus its resources on the demographics most likely to respond to the promotion. This paper reviews subjective and unclear marketing and sales activities that K telecommunication company operated, and introduces the whole process of developing the GIS information system. The process consists of the following 5 modules : (1) Customer profile cleansing and standardization, (2) Internal/External DB enrichment, (3) Segmentation of 3,074 legal regions into 46,590 sub_regions called blocks, (4) GIS data mart design, and (5) GIS system construction. The objective of this case study is to emphasize the need of GIS system and how it works in the private enterprises by reviewing the development process of the K company's market analysis and sales management system. We hope that this paper suggest valuable guideline to companies that consider introducing or constructing a GIS information system.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.177-192
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• 2012

This is a study of match-making systems that considers the mutual satisfaction of matching partners. Recently, recommendation systems have been applied to people recommendation, such as recommending new friends, employees, or dating partners. One of the prominent domain areas is match-making systems that recommend suitable dating partners to customers. A match-making system, however, is different from a product recommender system. First, a match-making system needs to satisfy the recommended partners as well as the customer, whereas a product recommender system only needs to satisfy the customer. Second, match-making systems need to include as many participants in a matching pool as possible for their recommendation results, even with unpopular customers. In other words, recommendations should not be focused only on a limited number of popular people; unpopular people should also be listed on someone else's matching results. In product recommender systems, it is acceptable to recommend the same popular items to many customers, since these items can easily be additionally supplied. However, in match-making systems, there are only a few popular people, and they may become overburdened with too many recommendations. Also, a successful match could cause a customer to drop out of the matching pool. Thus, match-making systems should provide recommendation services equally to all customers without favoring popular customers. The suggested match-making system, called Mutually Beneficial Matching (MBM), considers the reciprocal satisfaction of both the customer and the matched partner and also considers the number of customers who are excluded in the matching. A brief outline of the MBM method is as follows: First, it collects a customer's profile information, his/her preferable dating partner's profile information and the weights that he/she considers important when selecting dating partners. Then, it calculates the preference score of a customer to certain potential dating partners on the basis of the difference between them. The preference score of a certain partner to a customer is also calculated in this way. After that, the mutual preference score is produced by the two preference values calculated in the previous step using the proposed formula in this study. The proposed formula reflects the symmetry of preferences as well as their quantities. Finally, the MBM method recommends the top N partners having high mutual preference scores to a customer. The prototype of the suggested MBM system is implemented by JAVA and applied to an artificial dataset that is based on real survey results from major match-making companies in Korea. The results of the MBM method are compared with those of the other two conventional methods: Preference-Based Matching (PBM), which only considers a customer's preferences, and Arithmetic Mean-Based Matching (AMM), which considers the preferences of both the customer and the partner (although it does not reflect their symmetry in the matching results). We perform the comparisons in terms of criteria such as average preference of the matching partners, average symmetry, and the number of people who are excluded from the matching results by changing the number of recommendations to 5, 10, 15, 20, and 25. The results show that in many cases, the suggested MBM method produces average preferences and symmetries that are significantly higher than those of the PBM and AMM methods. Moreover, in every case, MBM produces a smaller pool of excluded people than those of the PBM method.