• Asia pacific journal of information systems
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• v.16 no.4
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• pp.239-254
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• 2006

Location-based advertising or application has been one of the drivers of third-generation mobile operators' marketing efforts in the past few years. As a result, many studies on location-based marketing or advertising have been proposed for recent several years. However, these approaches have two common shortcomings. First. most of them just suggested the theoretical architectures, which were too abstract to apply it to the real-world cases. Second, many of these approaches only consider service provider (seller) rather than customers (buyers). Thus, the prior approaches fit to the automated sales or advertising rather than the implementation of CRM. To mitigate these limitations, this study presents a novel advertisement recommendation model for mobile users. We call our model MAR-CF (Mobile Advertisement Recommender using Collaborative Filtering). Our proposed model is based on traditional CF algorithm, but we adopt the multi-dimensional personalization model to conventional CF for enabling location-based advertising for mobile users. Thus, MAR-CF is designed to make recommendation results for mobile users by considering location, time, and needs type. To validate the usefulness of our recommendation model. we collect the real-world data for mobile advertisements, and perform an empirical validation. Experimental results show that MAR-CF generates more accurate prediction results than other comparative models.

• The Journal of Economics, Marketing and Management
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• v.10 no.6
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• pp.27-37
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• 2022

Purpose: The purpose of this study is to derive various ways to realize customer satisfaction for the development of the service industry by exploring research trends related to customer satisfaction, which is presented as an important goal in the service industry. Research design, data and methodology: To this end, 1,456 papers with English abstracts using scienceON were used for analysis. Using Python 3.7, word frequency and co-occurrence analysis were confirmed, and topics related to research trends were classified through BERTopic and LDA. Results: As a result of word frequency and co-occurrence frequency analysis, words such as quality, intention, and loyalty appeared frequently. As a result of BERTopic and LDA, 11 topics such as 'catering service' and 'brand justice' were derived. As a result of trend analysis, it was confirmed that 'brand justice' and 'internet shopping' are emerging as relatively important research topics, but CRM is less interested. Conclusions: The results of this study showed that the 7P marketing strategy is working to some extent. Therefore, it is proposed to conduct research related to acquisition of good customers through service price, customer lifetime value application, and customer segmentation that are expected to be needed for the development of the service industry.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.79-87
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• 2010

This paper is proposed that implemental model of customer relationship management system for oriental hospital is designed by customer segmentation using personal information and medical record of outpatients in existing integrated medical information system database. Proposed model can be practical model at once, because it can construct by partial modification of existing medical information system without additional information technology and infrastructure. And, if we use the proper variable and method of customer segmentation according to marketing strategy, it can be flexible customer relationship management system not only improvement of customer satisfaction but also various marketing supports.

• Journal of the Korean Society of Food Culture
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• v.24 no.4
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• pp.413-418
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• 2009

Existing literature on the CRM [Customer Relationship Management] has emphasized the marketing strategies between the franchisor and franchisee. In this study, we focused instead on factors involved in forging relationships based on marketing strategies between franchisee and the customers. A survey questionnaire was completed by 250 customers of Korean-style food franchises located in Seoul and Inchon. Each questions is based on a 5-point likert-type scale. After initial data recording, 41 questionnaires were deleted from the data set because of missing or insincerely answer. Finally, the sample data of 209 questionnaires were used for the statistical analysis. The data were analyzed with SPSS version 13.0 software to assess consumer satisfaction, trust, and support/reputation on flexibility and commitment. Regression analysis was performed to analyze the relationship between flexibility and commitment. Satisfaction and support/reputation significantly influenced flexibility, both satisfaction and trust significantly influenced commitment, and both flexibility and commitment significantly influenced the restaurant-consumer relationship.

• Journal of Service Research and Studies
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• v.2 no.1
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• pp.39-46
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• 2012

It is growing in size of database in companies. This caused to develope data mining techniques to predictive information from the large database. Costs and other effects can give variety of sales exploding through the analysis of the differences. Analysis of the various classification techniques, various angle can be analyzed point of view of the area information. The analysis of rules and patterns associated with a large amount of useful information from the database can be analyzed effectively. Goods store were analyzed using association rules, one of the data mining analysis techniques. Through this type of existing products according to analyze customer buying patterns, data mining has been studied to establish strategic marketing analysis.

• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.99-108
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• 2006

대형 할인점 매출 데이터는 G-CRM, 에어기어 마케팅(Area Marketing)에 활용하기 위해 고객의 구매정보와 위치정보를 포함한다. TM중부좌표로 이루어진 고객 위치정보를 이용하여 지점간의 거리를 구할 수 있다. 서로 다른 위치에서 통시에 측정된 자료들이 공간적인 변인에 의하여 영향을 받는다면, 공간적인 변인의 함수식에 의한 예측모형을 설정하는 것이 타당하다. 본 연구에서는 공간적인 변인으로 거리가 주어졌을 때, 대형 할인점 매출 자료에 대한 세미베리오그램(Semi-Variogram)의 모형을 추정하고, 관측되지 않은 지역에 대한 할인점 이용권을 공간예측기법으로 예측하였다. 그리고 공간예측 기법을 통해 예측된 할인점 이용권을 토대로 할인점 이용권 지도를 작성하였다. 또한 매출 데이터의 공간이상치 탐지를 위한 방법을 제시하고 실례로 알아보았다.

• Fashion & Textile Research Journal
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• v.7 no.1
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• pp.4-12
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• 2005

The purpose of this study was to analyze the utilization of Fashion Brands Web-site. This analysis was done by 6C Concept(Contents, Community, Commerce, Connection, Customizing, Communication) which was Internet Marketing Strategy. The review of previous studies and empirical investigations through the Internet were processed for this study. 151 fashion brands in department stores in Daegu, Korea were surveyed from January to February 2004. Data were analyzed by using frequency and percentage. Total 105 brands established their Web-Sites of Internet out of 151(69.5%) fashion brands. There were four characters on Contents, six characters on Connection and five characters on Communication. And there were a establishing rate of 38.1 percent on Online Community and 30.5 percent on Online Shopping Mall. On Customizing, 73.3 percent of brands had e-CRM systems.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.1
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• pp.97-111
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• 2003

The purpose of this study is to identify the consumer's website attitude by product perception. There are a lot of benefits of some obstacles in the use of e-commence through the Internet-enabled website. The website or webpage is a marketing message for customers and many consumers use the Internet to acquire own informations. Indeed, it is necessary to construct positive attitude within an operating website, and IT is used as a useful tool for building the trust relationships with consumers. For eCRM in Internet era, it is very important to identify factors affecting consumer's website attitude. In sum, this study is focused the relationships between consumer's website attitude and product perception, brand attitude.

• Journal of the Korea Safety Management & Science
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• v.9 no.6
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• pp.31-38
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• 2007

The construction industry by its nature retains higher level of danger where the smallest of error may lead to a major catastrophe endangering many workers and public safety as well as provoke social criticism. With the aid of quantitative statistical data on safety-related calamity analyzed till this day, this paper handled in depth the analysis of diseases other than the accidents, and selected new variable indexes that influence the indirect sections of calamity that are mostly concealed and incorporated them in a new model. For the factor selection of new calamity evaluation model, FRAT(Frequency, Recency, Amount, Type of merchandise/service)technique of customer-related management in marketing was applied, and as for the significance of each factor in the weight selection of variables. Consequently, considering the graveness of the FRAT itself through safety management experts, the related researches must be expanded.

• IE interfaces
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• v.25 no.2
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• pp.229-240
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• 2012

Conventional research on customer relationship management(CRM) in general has focused on the effects of individual customer's satisfaction, retention and profit management. However, corporate customers are more profitable than individual customers because of high volume and frequent transactions between companies. In this article, a prototype for a corporate customer relationship management is developed in the postal service. First, the frequency and amount of customers' usage were examined, and thereby the corporate customer rating scheme was established to provide customized service. Second, five different types of usage patterns were determined using clustering analysis. In addition, we presented the rationales behind the five types of patterns. Third, RFM(recency, frequency, monetary) analysis was performed, and then action plans were developed to increase sales. Finally, the prototype software was developed to automatically perform the above analysis using MS Excel program.