• International Commerce and Information Review
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• v.15 no.4
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• pp.125-145
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• 2013

The Korea-EU FTA will provide korea with a significant advantage in the region both international trade and consumer welfare. Under the Korea-EU FTA, increasing of bilateral trade in consumer and industrial products would become duty and most remaining tariffs would be eliminated. This article studies on EU product price level of Korean consumer for before and after Korea-EU FTA effectuation. The questionnaires are sended 1,000 samples and 780 returns, 283 of them are analyzed for a this study. This paper has there main a parts, A Paired Samples Test result shows that the EU goods price level are positively affected by Flesh-meat, Electronic device & Electric home appliances, Kitchen utensils, Fruit juice(beverage), alcoholic liquors(wine, whisky), Clothes & Fashion. However, The Clothes & Fashion does not affect in EU goods price level, the Clothes & Fashion positively affected price differential more FTA effectuation before than FTA effectuation after.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2003.11a
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• pp.393-407
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• 2003

공동구매는 ‘가격절감’, ‘위험감소’, ‘거래비용 절감’, ‘참여의식’등의 장점을 가지고 있다. 이러한 장점은 소비자들로 하여금 구매형태에 직ㆍ간접적인 영향을 미치는 것으로 나타났다. 반면 ‘시간지연’, ‘제품다양성 부족’, ‘결제수단’, ‘상품디스플레이’등의 단점을 가지고 있다. 이러한 단점들 역시 소비자들로 하여금 구매형태에 직ㆍ간접적인 영향을 미치는 것으로 나타났으나 반면 한번 거래를 하게 되면 계속해서 거래를 한다는 의견과 앞으로도 거래를 할 생각을 가지고 있으며 주변의 다른 이들에게도 추천하겠다는 생각을 가지고 있었다. 장ㆍ단점과 관련하여 공동구매를 ‘재수용 하는가’와 ‘주변사람들에게 권유할 것인가’를 연구하였다. 본 연구의 목적은 공동구매 특성이 공동구매를 수용함에 있어서 지속적인 수용을 할 것인가와 더불어 주변의 사람들에게 권장을 하는가를 파악하는데 있다. 본 연구에 대한 자료 수집방법은 D대학교의 재학생들을 대상으로 총 100부를 설문 조사하였으며, 수집된 설문지 중에서 불성실하게 응답한 설문지 8부를 제외한 총 92부를 유효한 설문으로 확보하였다. SPSS_WIN 10.0 패키지를 이용하였으며, 대상을 통하여 제품별(종류별) 선호도와 구매시(저가격, 안전성, 배송, 시간절감, 결제편리, 기타) 우선순위를 빈도분석 하였다. 또한 요인분석통한 타당도와 신뢰도 분석하고, 연구변수로 선정한 각 요소들을 이용하여 공동구매의 특성(가격대비 성능, 편리성, 결제안전, 다양한 제품 제공)에 따라 공동구매 재수용도와 주변사람 들에게 권유할 것인가에 영향력 정도를 파악하기 위해 회귀분석을 실시하였다. 조사결과 제품 선호도의 측면에서는 서적&음반, 의류&신발, 컴퓨터&주변기기 가장 선호하는 품목으로서 전자상거래와 거의 흡사하게 나타났으며, 구매시 가장 중요하게 느끼는 요소는 저렴한 가격과 안전&안정성으로 나타났다. 또한, 공동구매 특성에 대한 요인분석 결과로는 하나의 독립요인으로 존재하지만 결재안전, 다양한 제품제공의 요인들이 편리성 요인의 하부요인으로 존재하는 것으로 나타났다. 공동구매 특성이 재수용과 주변사람 권유에 대한 결과로는 재수용적인 측면에서는 ‘가격대비 성능’과 ‘다양한 제품 제공’이 유의한 영향을 미칠 것으로 나타났으며, 주변사람 권유적인 측면에서는 ‘가격대비 성능’이 유의한 영향을 미칠 것으로 나타났고 재수용성과 다르게 ‘다양한 제품 제공’측면에서는 영향을 미치지 않는 것으로 나타났다.

• The Research Journal of the Costume Culture
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• v.32 no.2
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• pp.199-214
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• 2024

Until now, research on consumers' purchasing behavior has primarily focused on psychological aspects or depended on consumer surveys. However, there may be a gap between consumers' self-reported perceptions and their observable actions. In response, this study aimed to investigate consumer purchasing behavior utilizing a big data approach. To this end, this study investigated the purchasing patterns of fashion items, both online and in retail stores, from a data-driven perspective. We also investigated whether individual consumers switched between online websites and retail establishments for making purchases. Data on 516,474 purchases were obtained from fashion companies. We used association rule analysis and K-means clustering to identify purchase patterns that were influenced by customer loyalty. Furthermore, sequential pattern analysis was applied to investigate the usage patterns of online and offline channels by consumers. The results showed that high-loyalty consumers mainly purchased infrequently bought items in the brand line, as well as high-priced items, and that these purchase patterns were similar both online and in stores. In contrast, the low-loyalty group showed different purchasing behaviors for online versus in-store purchases. In physical environments, the low-loyalty consumers tended to purchase less popular or more expensive items from the brand line, whereas in online environments, their purchases centered around items with relatively high sales volumes. Finally, we found that both high and low loyalty groups exclusively used a single preferred channel, either online or in-store. The findings help companies better understand consumer purchase patterns and build future marketing strategies around items with high brand centrality.

• Journal of Korean Home Economics Education Association
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• v.22 no.2
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• pp.115-131
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• 2010

The object of this study is to compare the cognitive differences between teenagers who are operating the internet shopping mall and those who are not operating to analyze the effect of the enterprise experience on the career maturity of teenager. And we are to present the operation methods of teenager entrepreneurship education at school by identifying the difficulties of teenager internet shopping malls and investigating demands of teenagers for the entrepreneurship education. The results of this study are as following. First, the internet shopping malls established by teenagers were mostly operated with small scale and capital dealt with clothing and fashion accessories. It is difficult for most of teenagers to inform the shopping malls and understand the flow of fashion and demands of consumers. They acquired the informations on enterprise using internet or acquaintances. This is because there are no professional teenager entrepreneurship education. And they chose the confidence and spirit of challenge which are mostly needed for success of the internet shopping malls. Therefore, they can acquire the confidence and spirit of challenge by effective entrepreneurship education on resource management, team management, business plan and marketing. Second, teenagers who are operating the internet shopping malls got higher scores on career maturity and degree of need in the entrepreneurship education than those who are not. Thus the expansion of the systemed and diversified entrepreneurship education at school is needed to increase business practice and entrepreneurship. Third, most teenagers wanted the entrepreneurship education at school. They preferred external lectures who can teach them with professional experiences and practical knowledges using discretional activity classes or club activity classes. Dividend classes of creative experience activities including career, voluntary and club activities are increased in 2009 revised education curriculum. Using these classes, it requires to operate the entrepreneurship education which make students decide their career themselves through concrete education and experience. Consequently, the expansion of the systemed and diversified teenager entrepreneurship education at school is needed using development of practical entrepreneurship education program, professional teacher training and revitalization of entrepreneurship club activities.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.