• Science of Emotion and Sensibility
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• v.11 no.2
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• pp.181-192
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• 2008

The purpose of this study was to examine the outdoorwear satisfaction of silver consumers and their purchase behavior according to age. The survey participants in this study were 100 elders who were climbing the Bukhan mountain; 68 among them were new silver group in range of 55-64 years old. As the subjects were old people who had a relatively low level of cognitive ability, self-administration method and interview were employed together. The collected data were analyzed with t-Test and x2 -test. The results follow: the new silver group had purchased more and spent more money on outdoorwear. The brand recognition, purchase place, purchase criteria, and dissatisfaction factors of silver groups were different from those from new silver groups. The quality and design/color were thought to be needed for improvement for a new silver group, while quality and comfort/wearability were for silver group.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.11a
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• pp.226-227
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• 2009

본 연구에서는 구매 상황과 직접적 관련이 없는 특정 정서 상태가 상품 선택에 미치는 영향을 알아보고자 하였다. 상품 범주는 구매하고자 하는 물품을 대하는 태도로 분류된 실용적/쾌락적(utilitarian/hedonic) 물품 기준을 사용하였고, 동일한 시나리오 상황에서 특정 정서(긍정/부정/중립)에 따라 선택된 상품에 차이가 발생하는지를 살펴보았다. 그 결과, 중립적 정서 상황에 비해 부정적 정서 상황에서 실용적 목적을 지닌 상품을 선택하는 비율이 유의미하게 높았다. 이는 부정적 정서가 체계적이고 구체적인 정보 처리 과정을 촉진시킨다는 기존 연구 결과가 구매행동에서도 적용 가능함을 시사한다.

• 한국벤처창업학회:학술대회논문집
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• 2019.04a
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• pp.187-189
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• 2019

주택 가격이 최근 급등하면서 각종 정부정책이 쏟아져 나오고 있지만 주택 가격은 지역 별 편차를 늘리는 등 다른 문제점들을 양상하고 급등한 가격을 조정하는데 어려움을 겪고 있다. 주택을 선택하는 속성에는 다양한 기준이 존재하고 있어 단순한 정부 정책만으로는 해결하기 어려운 측면이 있다. 따라서 다양한 주택선택 속성에 대해 파악하고 주택구매 의도에 미치는 영향에 대해 파악하는 것이 중요하다. 본 연구는 주택선택 속성과 정부정책이 주택 구매행동에 미치는 영향력을 통해서 주택시장에 대한 이해를 돕고자 한다. 이를 위한 분석의 주요 쟁점은 다양한 유형의 주택선택 속성과 정부 정책 간에 부동산 투자전망의 조절효과를 고려하는 것이다.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.179-188
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• 2021

This study investigated the purchase status, wearing status, purchase satisfaction, selection criteria, and improvement marin leports wear for subjects who enjoy marine leisure sports in the southwestern region of Jeollanam-do, and examines the correlation between age and body type and the correlation between variables. SPSS Ver. 26.0 program was used for analysis. In the correlation between the motivation for participation and the selection criteria, when participating to increase physical strength, it was selected based on the fit. When participating for leisure or hobbies, they were selected based on design and color. The relationship between the selection criteria and purchase satisfaction was not satisfied in terms of price when they were selected based on activity or utilization of other uses. As for the selection criteria according to the body type, clothing was selected based on price and fashion for large triangles and squares, and elasticity for inverted triangles. As for the preferred color by age, only those in their 40s preferred blue and other age groups preferred achromatic color. In future studies, it is thought that a study on the preference of each marine leisure sports item should be conducted.

• Proceedings of the CALSEC Conference
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• 2005.11a
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• pp.147-153
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• 2005

When a customer wants to buy an item at the Internet shopping mall, one of the difficulties is to decide when to buy the item because its price changes over time. If the shopping mall can be able to recommend appropriate buying points, it will be greatly helpful for the customer. Therefore, in this presentation, we propose a method to recommend buying points based on the time series analysis using a database that contains past prices data of items. The procedure to provide buying points for an item is as follows. First, we search past time series patterns from the database using normalized similarity, which are similar to the current time series pattern of the item. Second, we analyze the retrieved past patterns and predict the future price pattern of the item. Third, using the future price pattern, we recommend when to buy the item.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2000.05a
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• pp.85-92
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• 2000

본 연구에서는 인터넷 쇼핑몰 패키지용 전자지불시스템에서 구매자가 인터넷상에서 안전한 지불을 하기 위해 사용하는 전자지갑인 CM-Wallet을 SET프로토콜기준에 따라 개발하였다. CM-Wallet은 RSA 1024bit, Triple DES 168bit 암호키 및 전자서명, 이중서명을 생성함으로서 메시지 보안도가 SET 기준을 만족하였다. 그리고, 복잡한 절차는 내부적으로 처리하여 구매자가 사용하기 쉽게 화면으로 보여지는 절차를 간소화하였으며, 전자지갑을 사용할 때 복잡한 절차에 대한 불편함을 해소하였다.

• 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.

• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.97-106
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• 2015

In recent, hybrid market segmentation techniques have been widely adopted, which conduct segmentation using both general variables and transaction based variables. However, the limitation of the techniques is to generate incorrect results for market segmentation even though its methodology and concept are easy to apply. In this paper, we propose a novel scheme to overcome this limitation of the hybrid techniques and to take an advantage of product information obtained by customer's transaction data. In this scheme, we first divide a whole market into several unit segments based on the general variables and then agglomerate the unit segments with higher QAP correlations. Each product network represents for purchasing patterns of its corresponding segment, thus, comparisons of QAP correlation between product networks of each segment can be a good measure to compare similarities between each segment. A case study has been conducted to validate the proposed scheme. The results show that our scheme effectively works for Internet shopping malls.

• Environmental engineer
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• v.18 s.189
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• pp.52-56
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• 2002

• 보일러설비
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• s.91
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• pp.117-122
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• 2001