• Fashion & Textile Research Journal
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• v.23 no.1
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• pp.70-83
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• 2021

Live-streaming commerce is attracting attention as a noticeable trend in the retail industry. It is a new mobile shopping service platform developed by combining live streaming with e-commerce technologies. This study examined the impact of para-social interactions on consumer impulse buying behavior and investigated the impact through task complexity as well as perceived amount of information. To achieve this goal, 203 women using a mobile commerce participated in an online survey after experiencing beauty live-streaming commerce. The collected data were analyzed using SPSS 25.0, AMOS 23.0, and SPSS PROCESS Macro program. The results of the study revealed that para-social interactions negatively influenced task complexity, positively influenced perceived amounts of information, and positively influenced impulse buying behavior. In addition, impulse buying behavior was negatively influenced by task complexity versus positively that was influenced by perceived amounts of information. The impact of para-social interactions on impulse buying behavior is mediated by task complexity and perceived information. The findings of this study contribute to the theoretical extension of para-social interaction on impulse buying behavior in the context of live-streaming commerce. The implications of the findings suggest practical marketing strategies for digital media commerce retailers.

• Fashion & Textile Research Journal
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• v.24 no.3
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• pp.279-288
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• 2022

This study aims to derive the need for middle-aged women to consider using fashion product applications, styling, and personalized styling services. To analyze the fashion styling considerations of middle-aged women, 200 women in their 40s and 50s were surveyed. Middle-aged women usually tend to shop through home shopping, department stores, fashion soho (Small office home office) malls, and open market-type applications, and purchase fashion products more than two or three times a month, spending an average of less than 50,000 won per month. Middle-aged women consider choosing appropriate clothing based on the occasion and place, complementing the flaws of the changed body type as well as taking into account the weather in the styling process, and seek to showcase a sophisticated, luxurious, and youthful image through styling. However, they are confused and face difficulties in fashion styling, with regard to not only overall body shape but also partial body changes, such as increasing waistline, flabby thighs and arms, and decreasing hip volume. In addition, middle-aged women were looking for expert advice on styling to help them look the best. They also wanted to solve the difficulties of making a right choice amid the overflowing information related to fashion. The results of the study contribute to identifying products that meet the needs of middle-aged women and help develop detailed consumer-tailored marketing strategies, thereby improving sales of fashion products.

• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.212-229
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• 2020

'Live + Sale' is actively promoted in China and 'Wang-Hong', also known as Chinese internet celebrities are dominating this format of marketing strategy recently. They introduce products to consumers through live broadcasts, promote online shopping, and frequently evoke impulsive buying. Under this context, it is worth focusing on what factors influence impulse buying during Wang-Hong's live broadcast. This study investigated the impact of Wang-Hong characteristics on impulse buying behavior when watching live sales. Also, the mediating role of flow experience and viewing satisfaction was explored. Furthermore, we expected that the different live broadcast circumstances could have a different impact on flow experience, viewing satisfaction, and impulse purchase. A total of 242 Chinese women who have experience of viewing live sales were recruited through a Chinese research platform. The results revealed that Wang-Hong's trustworthiness and attractiveness positively affected the viewer's impulse buying directly, and indirectly through flow experience and viewing satisfaction, whereas expertise did not have any impact on impulse purchase. However, there were no significant differences between the two live broadcast circumstances. This research can enhance understanding of the impulse buying process during Wang-Hong's live sale and help brands come up with effective influencer marketing strategies using live sales.

• The Research Journal of the Costume Culture
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• v.14 no.5
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• pp.790-801
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• 2006

This study analyzed features of elements that compose a logo of inner wear brands to get the following results: First, it was found that "elegance" was the most frequently used word to express the concept of inner wear brands to be followed by words like dignity, high-end and aristocratic, words emphasizing femininity, such as feminine, romantic and sexy, words emphasizing practicality, such as convenient, practical, modern, functional and reasonable, and words emphasizing hygiene, such as clean, healthy and hygienic. This suggests that consumers nowadays pursue image more than functional aspects in the shopping of inner wear and consumers' pursuit of such values is reflected in the concept of inner wear brands. Second, unlike logos for outerwear brands that generally used initials of brand name, word-type logos for inner wear brands used the full name of brands, thus suggesting that they put more emphasis on delivery of information rather than on the symbolic aspect. In case of combining characters with concrete objects, they were found generally to use objects that give an soft, elegant and feminine image, such as flowers, woman's head and ribbons. Third, colors in the series of pink and red seemed to be used to convey the concept of inner wear brands that pursue such images as romanticism, femininity, elegance and sensibility, while colors in the series of blue, black and grey for such concepts as functionality, practicality, simplicity, health, hygiene and refinement. With reference to typeface used in the design of logos, unlike outerwear brands of which 83% use sans serif typeface for logos, relatively high percentage of inner wear was found to use typefaces of serif series to stress feminine flexibility and delicacy and give the image of elegance and classical tenderness. With reference to language used in logo naming for inner wear brands, 33 brands were found to use English and only three brands used Korean among the 36 brands surveyed. Even with inner wear brand logos that have Korean name, it was found that they used English in the use of logo marks. Like the result of previous studies, the result of this study indicates that methods to design brand logos for clothing should be incessantly sought in a way to build brand power as an important component to represent concept or function of brands and reinforce brand image.

• Journal of the Economic Geographical Society of Korea
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• v.1 no.2
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• pp.21-42
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• 1998

This paper aims at examining the regional comparison of the business organization of retailing in the Seoul and Taegu metropolitan areas, as an attempt to understand regional structure of retailing within metropolitan areas which represents the suburbanization. On the national level, retail sales have concentrated on larger metropolitan area, the Seoul metroplitan area, the first largest metropolitan area, having higher sales for population scale. While the Taegu metropolitan area, the third largest metropolitan area, appears to lower retail sales for population scale. In order to confirm such phenomenon, this paper is to analyze and to compare the industrial composition of retailing by industry in 1991 of Seoul with that of Taegu. And this paper is to analyze the regional comparison of business organization of retailing: the percents of establishments under four employees, of juridical establishments, of employees of ordinary times, the annual sales per establishment of retailing. And the characteristics of business organization of retailing by industry are analyzed by principal components analysis, and the explanation of the types with component in each district(city, county, ward) is analyzed by cluster analysis(Ward method). The data of 1991 were obtained from the statistics in the Report on Establishment Census(Vol.3 Wholesale and Retail Trade) published by the National Statistics Office. The results are as follows: 1. The composition of retailing by industry in Seoul metropolitan area by annual sales in 1991 is characterized as appeared very higher composition rates of retailing of textiles, clothing, footwear and apparel accessaries', ‘retailing of furniture, home furnishings and equipment’, retailing of jewellery and watches’, ‘retailing of printed matter and stationery’, ‘retailing of personal transport equipment and gasoline service stations’, and ‘general merchandise stores’. But in Taegu metropolitan area, ‘retailing of food, beverages and tobacco’, ‘retailing of drugs, cosmetics and other chemical goods’, 'retailing household fuel’, and ‘genernal retail trade, n.e.c.’appears very high. Therefore Seoul metropolitan area has larger business scale and retailing of shopping goods has developed than Taegu metropolitan area.

• Journal of Distribution Science
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• v.6 no.1
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• pp.117-128
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• 2008

The purpose of the research is to furnish basic data for efficient and effective marketing by examining the correlation how a certain element effects on customer's selection behavior, when they choose private label branded clothes at the store of giant discount store like E-.mart, Home-plus, Lotte-mart and 2001 outlet. We come to the following conclusions through such procedures; What we found on this study is that main factors of decision related purchasing garment of private brand in giant discount store is based on the sales price, quality of products and needs of customer's using. Further to this, in terms of choice activity in private brand clothes, we realized the price value is depend on the resonable price with the items because nowadays most customers can be compare to other discount store around their shopping place including trend of garment and quality of products. The order of the general inclination in selection behavior of private branded garment in giant discount store is as follows; Sales price > style & trend > quality of product and substantial convenience > display and prompt buying. Judging from the conclusion of the research we noted that customer's satisfaction comes from their target price to supply substantial needs and in terms of styling of clothes should be considered current trendy compared to national brand as well.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.