• Proceedings of the Korea Association of Information Systems Conference
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• 2001.12a
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• pp.252-260
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• 2001

전자상거래는 우리나라 뿐 아니라 여러 선진국에서 새로운 비즈니스 환경으로 급속히 개발 되고 있으며, 아울러 기업에게 위협 요인과 동시에 새로운 기회로 다가오고 있다. 본 논문에서는 기존 전자상거래 모델에서 벗어나 쇼핑몰 관련 그룹을 제조. 유통. 생산업체인 공급자(B)그룹과 제품을 공급받아 소비자에게 직접 판매하는 도·소매(B)그룹 그리고 제품을 구매하는 소비자(C)그룹으로 나누고 서로 윈 윈(Win Win) 할 수 있는 효과적인 전자상거래 모델(B2B2C)의 사례를 연구하고자 한다. 이러한 기업 공동 B2B2C 전자상거래 모델을 웹 어플리케이션 전문제작회사인 D개발회사가 본 시스템 솔루션에 2개월을 소요·개발하여 적용한 결과 고객은 온라인-오프라인 상에서 상호적으로 대응 할 수 있었고, 제품에 대한 품질보증 역할을 더할 수 있어 기존 단골 고객을 중심으로 효율적인 수익을 창출 할 수 있는 전자 상거래 모델을 구축하였다. 즉, 기존의 오프라인의 점 조직 형태의 판매망을 통해 온라인 전자상거래와 상호 유기적으로 도움을 줄 수 있다. 이는 B2B2C의 새로운 전자상거래 모델 제시와 더불어 기존고객을 관리할 수 있는 CRM 도입 효과를 가져와 향후 전자상거래를 통한 온라인 유통망형성에 있어 새로운 솔루션 개발의 기반기술이 될 것이다.

• Journal of Global Scholars of Marketing Science
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• v.16 no.1
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• pp.45-71
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• 2006

Questionnaire data of 287 patrons of Tesco's Homeplus, Carrefour, Ermart, and Wal-rnart in the northern Daegu, Korea, using a structural equation model, were analyzed to investigate the hierarchical effects of values on discount store re-patronage intention as a measure of store loyalty, mediated by customers' evaluations of store associations. It was revealed that while customers' social affiliation value has a positive effect on store atmosphere evaluation, customers' self-actualization value has a positive impact on both after-sale service and employee services. It was also revealed that three associations such as access to a store, interior design, and employee services in their descending order have strong positive influences on the formation of customers' re-patronage intention. Theoretical and managerial implications are discussed in the conclusion.

• Journal of the Economic Geographical Society of Korea
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• v.8 no.2
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• pp.301-314
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• 2005

The purpose of this study is to inquiry specialized development strategies to revive the declining regional tourism in Japan, through the general characteristics of tourists and the evaluation of various tourism resources. Reaching its period of maturity after the bubble economy collapse, domestic tourism in Japan requires a change in quality of the regional tourism industry. The Kakeyu spa region, which has long history and abundant cultural resources, is specializing through rehabilitation strengthening theme of 'health seeking and recuperation'. The rate of the elderly women visitors is high in the Kakeyu spa, and the visitors use public transport and make a relatively long stay, because they want to recuperate their health or to cure their disease. In the evaluation of tourism resources, the visitors showed an increasing interest in the solemn temple scenery and the tranquil stroll road which are near by their lodgings. To reflect such demand characteristics, the Kakeyu community is actively developing the business such as rehabilitation, health-food development, voluntary service, and barrier free based on spa, culture, and nature.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.2
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• pp.1-9
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• 2015

In most techniques of information differentiating for data stream mining, they give larger weight to the information generated in recent compared to the old information. However, there can be important one among the old information. For example, in case of a person was a regular customer in a retail store but has not come to the store in recent, old information with the shopping record of the person can be importantly used in a target marketing for increasing sales. In this paper, highly attention itemsets(HAI) are defined, which mean the itemsets generated in the past frequently but not generated in recent. In addition, a twao-way decay mechanism and a data stream mining method for finding HAI are proposed.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.23-38
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• 2012

There is a large difference between purchasing patterns in an online shopping mall and in an offline market. This difference may be caused mainly by the difference in accessibility of online and offline markets. It means that an interval between the initial purchasing decision and its realization appears to be relatively short in an online shopping mall, because a customer can make an order immediately. Because of the short interval between a purchasing decision and its realization, an online shopping mall transaction usually contains fewer items than that of an offline market. In an offline market, customers usually keep some items in mind and buy them all at once a few days after deciding to buy them, instead of buying each item individually and immediately. On the contrary, more than 70% of online shopping mall transactions contain only one item. This statistic implies that traditional data mining techniques cannot be directly applied to online market analysis, because hardly any association rules can survive with an acceptable level of Support because of too many Null Transactions. Most market basket analyses on online shopping mall transactions, therefore, have been performed by expanding the co-occurrence criteria of traditional association rule mining. While the traditional co-occurrence criteria defines items purchased in one transaction as concurrently purchased items, the expanded co-occurrence criteria regards items purchased by a customer during some predefined period (e.g., a day) as concurrently purchased items. In studies using expanded co-occurrence criteria, however, the criteria has been defined arbitrarily by researchers without any theoretical grounds or agreement. The lack of clear grounds of adopting a certain co-occurrence criteria degrades the reliability of the analytical results. Moreover, it is hard to derive new meaningful findings by combining the outcomes of previous individual studies. In this paper, we attempt to compare expanded co-occurrence criteria and propose a guideline for selecting an appropriate one. First of all, we compare the accuracy of association rules discovered according to various co-occurrence criteria. By doing this experiment we expect that we can provide a guideline for selecting appropriate co-occurrence criteria that corresponds to the purpose of the analysis. Additionally, we will perform similar experiments with several groups of customers that are segmented by each customer's average duration between orders. By this experiment, we attempt to discover the relationship between the optimal co-occurrence criteria and the customer's average duration between orders. Finally, by a series of experiments, we expect that we can provide basic guidelines for developing customized recommendation systems. Our experiments use a real dataset acquired from one of the largest internet shopping malls in Korea. We use 66,278 transactions of 3,847 customers conducted during the last two years. Overall results show that the accuracy of association rules of frequent shoppers (whose average duration between orders is relatively short) is higher than that of causal shoppers. In addition we discover that with frequent shoppers, the accuracy of association rules appears very high when the co-occurrence criteria of the training set corresponds to the validation set (i.e., target set). It implies that the co-occurrence criteria of frequent shoppers should be set according to the application purpose period. For example, an analyzer should use a day as a co-occurrence criterion if he/she wants to offer a coupon valid only for a day to potential customers who will use the coupon. On the contrary, an analyzer should use a month as a co-occurrence criterion if he/she wants to publish a coupon book that can be used for a month. In the case of causal shoppers, the accuracy of association rules appears to not be affected by the period of the application purposes. The accuracy of the causal shoppers' association rules becomes higher when the longer co-occurrence criterion has been adopted. It implies that an analyzer has to set the co-occurrence criterion for as long as possible, regardless of the application purpose period.

• The Korean Journal of Franchise Management
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• v.3 no.1
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• pp.26-45
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• 2012

Market players have realized the importance of brand power and tried to develop effective marketing programs which focus on consumer's brand experience. This study aims to investigate brand experience and brand personality effect on brand attitude which is overall consumer's faith toward brands and repurchase intention in food-franchised by Structural Equation Model. As results, both brand experience and brand personality affect brand attitude although brand experience has more influence than brand personality. As consumers show positive brand experience and attitude, repurchase intention is higher. Brand attitude plays a mediation role in the relation of brand experience and personality, and repurchase intention. Also brand experience shows more influence than others on repurchase intention.