• The KIPS Transactions:PartD
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• v.14D no.4 s.114
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• pp.395-406
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• 2007

The development of e-commerce made a great effect on all the aspect of marketing mix. Especially, marketing stimuli of Halfplaza.com, excessive price discounts and auction by order of arrival, spread out gradually in internet shopping mall industry. The study showed that excessive price discounts combined with auction by order of arrival increased consumer's perceived value, but decreased perceived risk. In conclusion, legal protections must be established since consumers tend to be vulnerable to various marketing mix of deceptive e-commerce players.

• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.2
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• pp.287-304
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• 2016

This study examines the influence of product classification standards and structure on user perception as well as their attitude towards online shopping sites. The causal relationships of variables are also examined. The analysis was based on an online survey with 247 responses. Four types of internet shopping sites were developed and used as a stimulus. The results of the mean comparison analysis indicated that perceived variety, information overload, perceived shopping value and attitude towards the site varies significantly with product classification standards and structure. There was also of a marginally significant interaction between the classification standard and structure on perceived variety and information overload. The causal relationship analysis revealed that perceived variety positively influenced hedonic and utilitarian shopping value. However, information overload had a negative effect on hedonic and utilitarian shopping value. Both the hedonic and utilitarian shopping value positively influenced attitudes towards the sites. This study demonstrates that classification method influences customer perception and attitude. It offers interesting insights on a product classification method as a strategic tool for online shopping.

• The Research Journal of the Costume Culture
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• v.29 no.1
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• pp.1-15
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• 2021

The Internet of Things (IoT) has gained enormous popularity in various fields of industry. An IoT shopping environment is considered an effective tool for convenient use by consumers. Perceived values (including convenience and privacy risks) of IoT shopping can be the main factors that influence consumers' shopping intentions. The current study proposed a research model based on a value-based adoption model, which integrated perceived benefit and sacrifice, shopping attitude, and shopping intention in an IoT shopping environment. As potential customers, participants in their 20s and 30s were recruited through a marketing research firm. Responses collected via an online questionnaire validated the proposed research model and hypothesis. The results confirmed significant, positive relationships between perceived benefit, including both remote control and access convenience, and consumers' positive attitudes toward IoT shopping. The association between perceived privacy risk and consumers' shopping attitudes was not significant. The indirect effects of two benefits of IoT shopping on shopping intention were also significant and positive. From a practical perspective, this study can help marketers and service providers manage their IoT shopping platforms or applications more effectively to attract consumers. The implications and limitations of this study are discussed. Directions for future research and development of IoT shopping environment are suggested.

• Journal of the Korean Home Economics Association
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• v.45 no.5
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• pp.95-119
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• 2007

The purpose of this study was to investigate the shopping values(utilitarian and hedonic values) sought and the risks(economic, functional, socio-psychological, and privacy) perceived by consumers who participate in Internet auctions by determining the factors that affect their shopping values and risk perceptions. Empirical data were collected by an Internet survey of netizens who were interested in and had experience in Internet auctions. Questionnaires were distributed to the subjects through an Internet survey site and at an Internet auction cafe. A total of 300 questionnaires were analyzed. The results showed that consumers showed a slightly greater pursuit of a utilitarian value than a hedonic outcome in their Internet auction practices; however the outcomes pursued by consumers in their teens and twenties tended to be more hedonic than utilitarian. Consumers with a higher level of innovation, self-confidence in purchase, and need for information searching showed a greater pursuit of utilitarian and hedonic outcomes. The group of consumers with a higher expectation for legal protection pursued a more utilitarian outcome, whereas the group of consumers with higher influence from the reference group pursued a more hedonic outcome. The consumers showed that they perceived functional risk as boing most serious, followed by privacy risk, economic risk, and socio-psychological risk. Subjects with higher degrees of innovation, self-confidence in purchase and self-control perceived economic risk as critical. Functional risk was perceived to be highest in the group of consumers with self-control and a need for information searching, whereas socio-psychological risk was perceived to be highest in the group of consumers showing more self-control. Privacy risk was perceived to be highest in the group of consumers with a higher degree of innovation and lowest in both groups of higher and lower affection. Both economic and privacy risks were perceived to be lower in the group of lower pursuit of a hedonic outcome.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10c
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• pp.552-554
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• 1999

인터넷 상거래가 활성화되면서 기업들은 인터넷과 접목하여 자사의 이익을 극대화 하는 방안을 모색하고 있다. 소비재를 생산하는 기업 및 중간 상인들은 일명 "쇼핑몰"을 구축하여 기업 홍보와 더불어 제품 판매를 시행하고 있으며 특정 기업은 상당한 가치 창출을 한 것으로 알려져 있으나, 자본재를 생산하고 거래하는 기업에서는 인터넷의 가능성에 대한 확신의 부족으로 투자를 꺼리고 있는 실정이다. 본 연구에서는 자본재 제품에 대한 정보를 구축.검색하는 제품몰을 개발하여 자본재를 생산하는 중소기업체들에게 인터넷 사업의 기회를 제공하고, 구축된 제품 정보 데이터베이스를 이용하여 제품간 유사성을 바탕으로 제품 검색자(바이어)에게 제품 정보를 제공하고자 한다. 이 연구의 결과로써, 기업은 자사의 제품에 대한 사양.특징.기술력 등을 인터넷을 통해 홍보하고 타사의 유사제품에 대한 정보를 제공받음으로써 제품 경쟁력 제고에 도움이 되며, 바이어는 전체적인 제품을 하나의 사이트에서 검색함으로써 정보 검색에 따른 시간을 절약하고 원하는 제품 정보와 함께 유사제품 정보를 제공받음으로써 제품 구매 판단을 위한 유익한 정보 제공을 기대한다. 제공을 기대한다.

• Fashion & Textile Research Journal
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• v.9 no.6
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• pp.626-636
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• 2007

The purpose of this study is to find out the important factors and efficient strategies concerning internet marketing. The areas of study interest are, the characteristics of on-line shopping mall and the consumer shopping propensity. To do this, a 24-item Internet shopping mall characteristics and a 13-item consumer shopping propensity variables were developed to collect data from the 230 samples. The sample population composed mainly of, the college students and business man who had recent on-line shopping experiences on apparel goods. The 4-item satisfaction measure was used as the dependent variable. Also, a 11-item perceived shopping value measure was developed and measured to explore the mediating effect in the path between the endogenous and exogenous variables. Findings indicate that the characteristics of Internet shopping mall significantly contribute to the utilitarian shopping values, while the consumer shopping propensity contributes to the utilitarian and hedonic shopping values. In addition, the characteristics of internet shopping mall, the consumer shopping propensity, and shopping values are the good indicators for the consumer satisfaction.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.123-136
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• 2014

Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.

• Korea Information Processing Society Review
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• v.8 no.6
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• pp.38-43
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• 2001

본 고에서는 인터넷 쇼핑몰 기업들 중 신생기업들을 대상으로 이들의 기업환경에 맞는 데이터베이스 마케팅 방법론을 제시하고자 한다. 그러므로 데이터마이닝(Data Mining)을 이용하여 기존고객을 세분화한 다음 고객 개개인의 특성에 맞는 마케팅을 프로모션(Promotion)하고 신규고객을 획득할 때는 신규고객의 특성을 미리 예측하여 고객의 평생가치(LTV:Life Value)를 촉진하여 기업과 고객과의 관계성을 높이고, 기업은 안정된 고객층으로부터 수익을 창출하고, 기업으로부터 더 많은 혜택을 받게 하는 것에 대하여 연구하였다.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2002.11a
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• pp.125-135
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• 2002

With rapid growth and competition of electronic commerce through internet, various buying types and business models are being appeared In this paper, we studied group buying which is new business model to consumer and factors affecting on trust and participation of group buying. The following are the regression result of this study. First, factors affecting on trust of group buying were different from factors affecting on participation of group buying. Second, perceived reputation factor, familiarity factor and product value factor made a significant effect on participation of group buying. Third customer service factor didn't make a significant effect on both participation and trust of group buying. Fourth, product value factor made a significant effect on both participation and trust of group buying. Fifth trust of group buying made a significant effect on participation of group buying

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.11a
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• pp.125-135
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• 2002

With rapid growth and competition of electronic commerce through internet, various buying types and business models are being appeared In this paper, we studied group buying which is new business model to consumer and factors affecting on trust and participation of group buying. The following are the regression result of this study. first, factors affecting on trust of group buying were different from factors affecting on participation of group buying. Second perceived reputation factor, familiarity factor and Product value factor made a significant effect on participation of group buying. Third, customer service factor didn't make a significant effect on both participation and trust of group buying. fourth, product value factor made a significant effect on both participation and trust of group buying. Fifth trust of group buying made a significant effect on participation of group buying