• Journal of Digital Convergence
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• v.13 no.6
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• pp.125-132
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• 2015

It is current situation that a number of issues are being raised how the weight is calculated from customer satisfaction survey. This study investigated how the weight of satisfaction for each quantile is different by comparing ordinary least square regression model to quantile regression model and carried out bootstrap verification to find the influence difference of regression coefficient for each quantile. As the analysis result of using R(Quantreg package) that is open software, it appeared that there was the influence size of satisfaction factor along study result and quantile and there was the significant difference statistically regarding regression coefficient for each quantile. So, to use quantile regression model that offers the influence of satisfaction factor for each customer group along satisfaction level would contribute to plan the quantitative convergence policy for customer satisfaction.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.177-197
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• 2001

This paper is aimed at proposing a data mining-driven analysis to manage the customer defection rate in the bank. After 1997 IMF crisis, Korean banks were suffering from hard-pressed restructuring. At the heart of such restructuring effects, there was the need to manage the customer more effectively than ever. So far, many banks in Korea used to a poor management of customers without any highly-skillful techniques. In line with this argument, we propose several data mining techniques to determine more effective technique far managing customer deflection. We applied three data mining techniques such as logit model, neural network, and C5.0. Experiment data were collected from personal deposit account data of a specific bank in Korea. After experiments, we found that C5.0 showed more robust performance compared to other two techniques. On the basis of those experiment results, we proposed customer defection management policy.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.371-378
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• 2018

The purpose of this study is to classify the customers according to the characteristics of the relational benefits and to compare the performances of the sub-groups. As a result of the research, the group type according to the relational benefits was subdivided into 3 groups, and each group was named emotional relational group, continuous relational group and intermittent relational group considering customer characteristics. First, the emotional relational group is the group that emphasizes the empathy and assurance between the service provider and the customer, and the continuous relational group is the group with the highest social, confidence and economic benefits. The intermittent relational group was simply a transaction-oriented group. This implies that a differentiated customer management strategy is needed for each relational benefit group based on customer experience in medical services.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2003.11a
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• pp.55-65
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• 2003

Since 1990s, despite the emergence of innovative telecommunication services in accordance with technological changes, only few services have attained satisfactory number of subscribers, and create revenues. As with other products or services, the possibility for the success of new telecommunication services is low, thus a systematic business strategy by businesses is required to achieve market success with broadband wireless Internet. For the current broadband wireless Internet to successfully enter the early market with an early growth, a customer oriented market strategy and service provisioning strategy is inevitable. In this study based on the market survey of individuals and business customers, the customer demand and related needs of broadband wireless Internet have been analyzed in depth. Then with the analysis and establishment of the killer applications and market segmentation, market development strategy is proposed.

• Korea Journal of Hospital Management
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• v.7 no.4
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• pp.152-171
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• 2002

The research objective is segmenting outpatients for CRM(Customer Relationship Management) in medical service. Using modified RFM(Recently, Frequency, Monetary) method based on frequency and profitability in the hospital, the data were analyzed with the data mining technique. The result can be summarized as follows : The outpatients were semented into the four groups: 1) the loyal patient group, who have kept visiting until recently and give high profitability; 2) potential loyal patient group, who give lower profitability but high frequency of use, 3) potential withdrawer patient group, who have lower frequency of use but give high profitability and; 4) withdrawer patient group, who give low frequency of use and have not visited recently.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.05a
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• pp.274-282
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• 2005

Customer retention is one of the major issued in life insurance industry, in which competition is increasingly fierce. There are many things to do to retain customers. One of those things is to be continuously in touch with all customers. The objective of this study is to design the contact scheduling system(CSS) to support the planers who must touch the customers without having subjective information. Support-planers suffer from lack of information which can be used to intimately touch. CSS that is developed in this study generates contact schedule to touch customers by taking into account existing contact history. CSS has a two stage process. In the first stage, it segments customers according to his or her demographics and contract status data. Then it finds typical pattern and pattern is combined to business rules for each segment. We expert that CSS would support support-planers to make uncontacted customers' experience positive.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.06a
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• pp.261-281
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• 2001

IMF이후로 우리나라의 은행들은 현재 큰 구조조정을 맞이하고 있으며 이 속에서 살아남기 위하여 기존의 고객의 유형을 분석하고 이를 마케팅 전략에 활용하는 연구의 필요성이 높아지고 있다. 기존의 만은 연구들이 은행 고객들의 유형을 설문지 분석방법에 의존하여 몇 개의 군집으로 분류하고 이들의 집단 및 특성을 연구하였다 하지만 설문데이터의 경우 고객들의 실제적인 행동이 반영되지 못하는 한계점을 가지고 있다. 이에 본 연구에서는 C은행의 실제 고객 자료를 통하여 다양한 데이터마이닝 기법을 적용하여 고객을 세분화한 다음 고객이 가계성예금을 해지하고 다른 은행으로 이탈하는 집단의 특성을 분류하고 규칙을 도출하였다. 또한 이들을 관리하는 전략을 제시하였다.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.531-538
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• 2005

In k-means clustering, we standardize variables before clustering and iterate two steps: units allocation by Euclidean sense and centroids updating. In applications to DB marketing where clusters are to be used as customer segments with similar consumption behaviors, we frequently acquire additional variables on the customers or the units through marketing campaigns a posteriori. Hence we need to modify the clusters originally formed after each campaign. The aim of this study is to propose a revision method of k-means clusters, incorporating added information by weighting clustering variables. We illustrate the proposed method in an empirical case.

• Proceedings of the Safety Management and Science Conference
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• 2000.05a
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• pp.393-410
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• 2000

For the development of chinaware having korea culture, using marketing survey and questionnaire to analysis of the preference and attitude of customer, and expends marketing share by market segmentation and price differentiation. This study is present to marketing strategy by making the plan of sales promotion for the development of industry chinaware of Yeoju and Icheon area.

• Proceedings of the Technology Innovation Conference
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• 2000.06a
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• pp.105-120
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• 2000

Rapid spread of Internet, there appear so many commercial wedsites. Websites are not only tools to advertise a company or a product, but also value-added products inself. So we need a systematic approach(planning, design, implementation) to develop a website. But existing reserches on website development have corvered only technological issues such as network and HCI(Human Computer Intercation). In this research a framework is proposed to develop a website systematically using database of existing websites. This framework is composed of several stages-target customer segmentation, determination of services on website, dtermination of business model, functinal positioning, and evaution.