• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.7
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• pp.1005-1014
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• 2002

The purpose of this study was to examine the effects of retail area image and shopping mall image on consumer behaviors in the retail area and in the shopping ma]1. Data were obtained from a survey to a stratified sample selected at the exits of five different malls. A total of 740 questionnaires were distributed, and 661 responses were analyzed. Stepwise regression analysis revealed that two retail area image factors of variety of stores and atmosphere significantly affected all three consumer behaviors (shopping, service facility visits, social activities). Stepwise logistic regression showed that facility and atmosphere of the retail area image and product & service and convenience of the fashion shopping mall image affected seven consumer behaviors in the shopping mall. The results indicate that the retail area image as well as the shopping mall image affects a variety of consumer behaviors in the shopping mall though no shopping mal1 image affects behaviors in the retail area.

• Asia pacific journal of information systems
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• v.11 no.4
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• pp.135-153
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• 2001

Internet business is transforming the current structure and way of shopping behaviors. As a frontier area of internet business, internet shopping mall industry is influenced by this trend. In this shopping situation, shopping objects and information on the object are separated, which makes consumers to decide on the contents and marketing function offered by the shopping mall. This study proposes an integrated model including the influencing factors on customer royalty in Internet shopping environments. Eight hypotheses are proposed based on previous research in Internet marketing and information systems. The results are quite supporting the model and hypotheses. The contents structure, marketing activities, and customer satisfaction in the internet shopping environment influence shopping experience, next purchases and reference to other people. The proposed model and empirical results would contribute to setting up strategy of Internet shopping mall industry, and also to future research in information systems and Internet marketing.

• The Research Journal of the Costume Culture
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• v.25 no.1
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• pp.1-15
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• 2017

Social commerce is a kind of internet shopping mall in which consumers purchase the products with other consumers through mutual interactions including the development of SNS(social network service). Social commerce has expanded rapidly as a mainstream online shopping mall over the past five years driving consumers to purchase more fashion products providing the cheaper prices than open market internet shopping mall. The purpose of this study is to identify the important parameters of social commerce characteristics and consumer characteristics that affect repurchase intention and word-of-mouth intention. A 221 survey questionnaire was distributed to men in their 20's and 30's who live in Seoul metropolitan area. The data were analyzed utilizing Cronbach's ${\alpha}$, factor analysis, and regression analysis using the SPSS 18.0 program. The results revealed, first, that in terms of social commerce characteristics, three variables(website reputation, interactivity, and product scarcity) influenced repurchase intention. Among them, website reputation identified as the most important factor influencing repurchase intention and word-of-mouth intention. Second, with regard to consumer characteristics, interest and a tendency toward impulse buying affected the repurchase intention, and interest and internet shopping experience have influenced the word-of-mouth intention. Among three variables interest in social commerce identified as the key factor affecting both repurchase intention and word-of-mouth intention. The results of the study provide the practical implications and suggest the business strategies to enhance social commerce in the future by identifying the key social commerce characteristics and consumer characteristics that influence male consumers' buying behaviors.

• Fashion & Textile Research Journal
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• v.6 no.5
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• pp.618-624
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• 2004

This study is to explore how consumers' needs for tactile cues affect their purchasing behaviors in the internet shopping mall. Since previous studies about internet shopping malls are mainly performed on the primary factors of perceived risk, there are insufficient studies of tactile cues for apparel products. Emphasis of this study is placed on verifying the following hypothesis; it is expected that consumers' needs for tactile cues affect apparel purchasing behaviors in internet shopping. The questionnaire was administered to 20 to 30 year old male and female respondents who are either students or businessmen living in the Busan area. 150 questionnaires were completed and collected for data analysis. The data were, using SPSS 10. 0 for Window, statistically analyzed by frequency and factor analysis for VARIMAX, Cronbach's coefficient and Linear regression analysis. Data were, using SPSS 10. 0 for Window, statistically analyzed by frequency and factor analysis for VARIMAX, Cronbach's coefficient, and ANOVA. The results of data analysis are as follows: First, the tactile cues negatively affect purchase intentions of consumers. This shows that apparel internet shoppers who have high desire for tactical cues tend to avoid purchasing products through the internet. Second, the factor analysis of the moderating effect on perceived risks shows that the perceived risks significantly moderate both the tactile cues and purchase intention of consumers. Third, analysis of purchased experience also shows that purchased experiences significantly moderate both the tactile cues and purchase intention.

• Management & Information Systems Review
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• v.4
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• pp.349-374
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• 2000

With rapid advances on Interactive technology, and the growing popularity of the Internet, Internet shopping receives considerable attention in both the popular-press and academic journals. The Internet has enormous commercial possibilities. But it is a new and dynamic medium that poses special challenges for marketers. The revolutionary nature of the Internet mandates that established wisdom on consumer marketing along with marketing-mix strategies has to be reexamined and perhaps radically revised. In order to assist marketers in this endeavor it is critical to understand consumers' buying behaviors of Internet shopping. But research in this area still very much its infancy. This study examined previous researches of Internet shopping and developed conceptual framework of Internet shopping modes. Additionally, this study examined empirical investigation of Internet shopping. Preliminary results suggests that there are significant differences in individuals' perceptions of Internet shopping and traditional shopping modes. Various factors influences on consumers' buying behavior on Internet shopping. There are Individuals' factors(personality, lifestyle, prior experience, perceived risk etc), shopping mall factors(trust, vividness, security, promotion, etc), product characteristics(product category, brand, etc), situational factors(time pressure, locational constraints etc), social/cultural factors(Norms, importance of other peoples etc). Additionally, We conducted empirical study of the impact of the Internet on consumer shopping behavior. We gathered consumers' reactions via an open-ended survey using a sample of 90 shoppers. We related the reactions to the factors of consumers' satisfaction or dissatisfaction of the Internet shopping. Consequently, there are many questions regarding factors that might influence Internet shopping. From theoretical and practical perspectives, studies that examine these factors would seem to offer much to the discipline. This paper has attempted th provide insights and direction of future empirical examination of Internet shopping.

• The Journal of Society for e-Business Studies
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• v.13 no.3
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• pp.21-49
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• 2008

The area of the internet shopping mall heavily relies on new emerging information technologies, and it essentially requires delicate marketing model to support consumer behavior. RSS, which is one of the representative Web 2.0 technologies, is the system that distributes digital contents without any Web browser. RSS is expected not only to be very useful in online marketing but also to become actively applied on various areas such as online newspapers and blogs. AISAS model was proposed to complement the AIDMA model that did not cover the new changing customer behaviors of online commerce environment such as search and share. In this research, we propose a marketing model which utilizes RSS based on the AISAS model to support internet shopping malls. With our marketing model, internet shopping malls are expected to provide required services to the customers at every AISAS step. Moreover, it can provide integrated services by connecting all service components of each step. We utilized RSS in our model to implement those services because RSS has many advantages on supporting search and share of product information.

• Management & Information Systems Review
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• v.37 no.2
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• pp.23-42
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• 2018

As the development of the Internet in China has led to the active shopping of the internet, the number of Chinese internet users and online shopping malls is increasing rapidly. Chinese internet shopping malls are experiencing satisfaction and discontent with their websites. Research has focused on the satisfaction of customers using internet shopping malls and internet shopping malls reported complaints to users as complaints about products and websites. The study looked at seven area Chinese internet users (Beijing, Harbin, Shenyang, Ganssu, Xian, Shanghai and Henan). The effect of product complaints and site complaints on shopping attitudes and behaviors of internet shopping users was studied, and economic benefits were studied as a control variable. As a result, There was no effect on controlling the economic benefits of the complaint against the product, but the controlling the economic benefits of the complaint on the site was effect. About 83 percent of those surveyed were in their 20s and 30s who had experience shopping online and in internet. And It is intended to present theoretical reviews and guidelines for Korean internet shopping malls operating here, as they plan to expand to China by analyzing their internet shopping mall users.

• 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.