• Journal of the Korean Society of Clothing and Textiles
• /
• v.32 no.8
• /
• pp.1274-1285
• /
• 2008

The purpose of this study is to investigate influences of perceived price dimensions and store attributes on store choice behavior. Three major retail formats, department store, discount store, and internet shopping mall in retail industry were compared with respect to store attributes and intention to purchase fashion products. Data were obtained from 427 consumers aged 25-49 years old. The results were as follows. (1) Multidimensional aspects of the price construct were identified: price-quality schema, prestige sensitivity, price mavenism, value consciousness, price consciousness, and sales proneness. (2) Store attributes included product assortment, quality per price (Q/P), service, and symbolic image in general. However, store attribute factors of three retail formats consisted of slightly different items. Department stores presented the highest level of mean scores on product quality, customer service, and symbolic images, while internet mall exhibited highest on product variety, information comparison, and quality per price. (3) Respondents presented high level of intention to purchase fashion products at internet mall, department store, and discount store in that order. (4) Purchase intention at department store was predicted by Q/P, service, symbolic image, prestige sensitivity, product assortment, clothing consumption, and age in order. Purchase intention at discount store was influenced by assortment & Q/P, symbolic image, clothing consumption, and sales proneness, whereas internet mall was predicted by product assortment, Q/P, service, price mavenism, and price-quality schema.

• The Research Journal of the Costume Culture
• /
• v.13 no.2 s.55
• /
• pp.209-220
• /
• 2005

The purposes of this study were to determine the components of internet shopping value and to identify how those influence on the consumers' internet shopping behavior of apparel products. The data were collected via a self-administered questionnaire from 221 male and female students who have the shopping experiences for apparel products on the internet shopping malls, living in Kyongnam province. Using SPSS 12.0 package, $Cronbach's \alpha$, factor analysis, cluster analysis, ANOVA, Duncan multiple range test and stepwise multiple regression analysis were performed. The results could be summarized as follows; 1) According to the internet shopping values, college student consumers were classified into three groups, utilitarian value shoppers, hedonic value shoppers and low interest shoppers. 2) As a results of the ANOVA among the three groups, significant differences were found in the internet shopping mall attributes and perceived risks. 3) Internet shopping values-hedonic and utilitarian shopping values, internet shopping mall attributes and perceived risks had an significant effect on the attitude and purchasing intention of the internet shopping mall.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.15 no.1
• /
• pp.123-138
• /
• 2013

This paper studied the apparel product attributes that women in the new elderly generation require in formal wears and in casual wears. The purpose of this study was to provide the design guideline when considering the changing and diverse buying patterns of the new elderly female consumers as opposed to the traditional elderly generation. We employed a qualitative study methodology of one-on-one in-depth interview with open coding. Between August 10 and October 3 of 2012, we interviewed sixteen female consumers of age 60 or above residing in the metropolitan area who considered themselves as young-minded. Our findings were as follows: The consumer-required attributes that the new elderly women wanted to present have five dimensions of symbolism, aesthetic, fitness, usefulness, and maintenance. The main focus of the apparel product attributes that the new elderly women wanted was the dimension of symbolism in formal wears and the dimensions of usefulness and maintenance in casual wears. The new elderly females were the emerging group of consumers of diversified clothing products who emphasized overall balance and wore appropriately for occasions. Apparel products for the new elderly females should incorporate the design attributes that they want as well as the overall balance among individual wears.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.29 no.9_10 s.146
• /
• pp.1349-1358
• /
• 2005

Generally apparel products were recognized as an incongruent product type which direct search was needed for. But nowadays apparel products were ranked as a second product type next to electronics in sale amount of internet shopping mall. Therefore more detailed study on which attributes of fashion products are more successful and suitable in internet shopping mall is necessary. This study was executed to analyze common attributes of successful apparel in internet shopping mall on the basis of real sale data, and then to help internet apparel marketer plan marketing strategies more efficiently. Common attributes of successful apparel products in internet shopping-mall in terms of product, price and promotion attributes were identified. 240 products which were loaded in bestseller section of internet shopping-mall for 8 weeks from November to December, 2004 were analyzed. The results are as follows. First, products ratio for women ($76.7\%$) were higher than for men($18.3\%$). And the amount of each apparel product types purchased by consumers were ranked in the order of leather/fur coat, woven coat, inner wear, jacket, T-shirts, pants, training wear, suit, knit wear etc. and basic style dominated in $74.2\%$. General brands ($69.2\%$) that had price competitiveness were preferred to famous designer brand, national brand and PB brand. Preferred level of price was ten thousand to fifty thousand won. For promotion skill, in order of just one product, product adding promotion product and package set were preferred. Regular price, less than $50\%$ off and more than $50\%$ off price showed no difference in preference. Product planning strategy for internet apparel marketer was followed on the basis of these results.

• Korean Journal of Human Ecology
• /
• v.21 no.6
• /
• pp.1185-1198
• /
• 2012

The purposes of this study were to investigate the relationships between e-loyalty formation process and satisfaction for apparel products by testing the research model developing upon prior researches, and to analyze the differences of the structural model between two groups (high satisfaction group and low satisfaction group). A total of 356 respondents participated through a convenience sampling at universities in Busan. Data were analyzed by a structural equation model analysis. The results were as followings: First, for the structural model, the attributes of shopping malls (e.g., e-store attributes and product attributes) affected consumer satisfaction which influenced the e-loyalty of shopping malls, mediated by value perception. Second, high-satisfaction group evaluated more importantly the attributes of shopping malls, higher perceived the value of products and web sites, more satisfied the mall, and had greater loyalty of online shopping malls than low-satisfaction group. Third, there were significant differences between high-satisfaction group and low-satisfaction group in the e-loyalty model for apparels. Specifically, for high-satisfaction group, the e-store attributes were more likely to influence the value perception of products and web sites than low-satisfaction group, while low-satisfaction group was the higher perceived the value of products, the more they satisfied and then the greater e-loyalty respectively. According to the findings, the implications and future suggestions related to e-loyalty of shopping malls for apparels are provided.

• Journal of Fashion Business
• /
• v.27 no.3
• /
• pp.50-62
• /
• 2023

The e-commerce fashion market has experienced a remarkable growth, leading to an overwhelming availability of shared information and numerous choices for users. In light of this, chatbots have emerged as a promising technological solution to enhance personalized services in this context. This study aimed to develop user-product attributes for a chatbot-based personalized fashion recommendation service using big data text mining techniques. To accomplish this, over one million consumer reviews from Coupang, an e-commerce platform, were collected and analyzed using frequency analyses to identify the upper-level attributes of users and products. Attribute terms were then assigned to each user-product attribute, including user body shape (body proportion, BMI), user needs (functional, expressive, aesthetic), user TPO (time, place, occasion), product design elements (fit, color, material, detail), product size (label, measurement), and product care (laundry, maintenance). The classification of user-product attributes was found to be applicable to the knowledge graph of the Conversational Path Reasoning model. A testing environment was established to evaluate the usefulness of attributes based on real e-commerce users and purchased product information. This study is significant in proposing a new research methodology in the field of Fashion Informatics for constructing the knowledge base of a chatbot based on text mining analysis. The proposed research methodology is expected to enhance fashion technology and improve personalized fashion recommendation service and user experience with a chatbot in the e-commerce market.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.4 no.2
• /
• pp.103-126
• /
• 2002

The purpose of this study was to examine the consumer's quality evaluation on the apparel of adult males and females. A demonstrative study was conducted using a questionnaire on adults over 20 years old who were considered to afford to purchase clothes. A total of 380 questionnaires were used for the demonstrative analysis. The study used SPSSWIN V.8.0 for the analysis. Frequency analysis, ANOVA, t-test, multiple regression analysis, and duncan test are executed. The study result is as follows: First, 19 attributes of customer quality perception are grouped into 2 categories of satisfier, dissatisfier factor by the role of each attribute. Second, significant differences are found partly in quality indications- including fabric compositions, sizes, fabric care, manufactured-place, and the place of origin, the importance degree of indication and general satisfaction in quality indicating system.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.36 no.10
• /
• pp.1087-1099
• /
• 2012

This study investigated the purchase intention of green fashion products based on Rogers' Diffusion of Innovation theory and compared the differences between Korean and British consumers. In order to identify the impact of personal characteristics, this study also examined the effects of fashion innovativeness and LOHAS tendency on perceived attributes of innovation and intention to purchase. With a convenience sampling method, a survey questionnaire was distributed at popular fashion streets in each country. A total of 426 data were obtained, 203 from the UK and 223 from Korea. About 52% were females, and 69% were in their twenties. A factor analysis generated two LOHAS factors (health concerns and eco concerns) and four attributes of green fashion products (image improvement, symbolic superiority, observability, and compatibility). Two types of green fashion products (organic cotton t-shirts and organic cotton t-shirts with an environmental message) were provided to measure the purchase intention, respectively. The findings were as follows. British consumers were more likely to show LOHAS tendency and to perceive positive advantages of green products compared to Koreans; in addition, British consumers presented higher mean scores on the purchase intentions of organic cotton products. Fashion innovativeness was significant to predict image improvement and symbolic superiority, while eco concerns were significant in compatibility for both nations. Compatibility was important for both countries in order to explain the intention to adopt two types of organic products. In addition, image improvement was another predictor for purchase intention of organic t-shirts with an environmental message. Managerial implications were provided.

• Fashion & Textile Research Journal
• /
• v.15 no.4
• /
• pp.533-542
• /
• 2013

Fashion products are frequently purchased on impulse and are also one of the most popular product categories sold online. Online environment attributes can facilitate flow experiences that are described as an optimal psychological state reached during an engagement in activities (e.g., games and e-shopping). This study estimated the path model to examine the causal relationships among shopping mall attributes, flow, e-impulse buying, and consumer satisfaction for fashion products. A total of 598 usable questionnaires were obtained from college students who had purchased fashion products through the Internet. Data were analyzed by exploratory factor analysis, confirmatory factor analysis, and path analysis using SPSS 18.0 and AMOS 18.0. The results showed that e-shopping mall attributes (visual attributes and product attributes) significantly influenced e-impulse buying (fashion-oriented impulse buying and promotion-oriented impulse buying) which was mediated by the consumer flow experience and then influenced by consumer satisfaction. In the path model, the flow was stimulated by shopping mall attributes, the e-impulse buying was influenced by flow, and the consumer satisfaction was influenced by e-impulse buying. Flow was the most highly related to the fashion-oriented impulse buying, and followed by the relationship of the flow and promotion-oriented impulse buying in the context of e-shopping for fashion products. A managerial implication was discussed for fashion product e-retailers to develop strategies on visual attributes and product attributes that could stimulate and increase the consumer flow to trigger impulse buying as well as consumer satisfaction.

• Smart Media Journal
• /
• v.10 no.1
• /
• pp.116-123
• /
• 2021

Due to the rapid growth of the online fashion market and the resulting expansion of online choices, there is a problem that the seller cannot directly respond to a large number of consumers individually, although consumers are increasingly demanding for more personalized recommendation services. Images are being tagged as a way to meet consumer's personalization needs, but when people tagging, tagging is very subjective for each person, and artificial intelligence tagging has very limited words and does not meet the needs of users. To solve this problem, we designed an algorithm that recognizes the shape, attribute, and emotional information of the product included in the image with AI, and codes this information to represent all the information that the image has with a combination of codes. Through this algorithm, it became possible by acquiring a variety of information possessed by the image in real time, such as the sensibility of the fashion image and the TPO information expressed by the fashion image, which was not possible until now. Based on this information, it is possible to go beyond the stage of analyzing the tastes of consumers and make hyper-personalized clothing recommendations that combine the tastes of consumers with information about trends and TPOs.