• Fashion & Textile Research Journal
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• v.23 no.3
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• pp.358-369
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• 2021

This study aims to classify the dimensions of the sales information of secondhand clothing goods on the C2C secondhand trading platform and to systematically analyze the components of each dimension. To this end, the NVivo 12.0 qualitative data analysis software was used. The content analysis showed that the sales information of secondhand clothing goods was classified into four dimensions: detailed information of the sale goods, information specific to secondhand clothing goods, seller opinion information, and service information. The components of each dimension were as follows. The detailed information of the sale goods included size, sale price, item, design, brand name, material, color, wearing season, fit, gender, etc. The information specific to secondhand clothing goods included the number of times the item was worn, its purchase history, and product condition. Seller opinion information included product review, sales motivation, notes for the transaction, coordination proposal, and usage proposal. The service information included the transaction mode, exchange·return·refund, and promotion. The frequency analysis showed that the highest frequencies were sale goods(37.47%), information specific to secondhand clothing goods(24.63%), seller opinion information(20.54%), and service information(17.37%). This study will help C2C secondhand trading platform managers or sellers establish clear standards for presenting sales information and developing ideas toward constructing differentiated platform contents.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.17-22
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• 2024

This paper introduces the implementation of a secondhand clothing trading system equipped with virtual fitting functionality based on deep learning. The proposed system provides users with the ability to visually try on secondhand clothing items online and assess their fit. To achieve this, it utilizes the Convolutional Neural Network (CNN) algorithm to create virtual representations of users considering their body shape and the design of the clothing. This enables buyers to pre-assess the fit of clothing items online before actually wearing them, thereby aiding in their purchase decisions. Additionally, sellers can present accurate clothing sizes and fits through the system, enhancing customer satisfaction. This paper delves into the CNN model's training process, system implementation, user feedback, and validates the effectiveness of the proposed system through experimental results.

• Fashion & Textile Research Journal
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• v.24 no.1
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• pp.66-80
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• 2022

Even before the Covid-19 outbreak, the second-hand fashion market has been growing as the fashion industry strives towards sustainability. It has also accelerated due to the economic contraction caused by the pandemic. In previous studies, the second-hand market has been steadily studied; however, the research is insufficient compared to the diversified market. Therefore, this study investigates changes in consumers' perception of the second-hand fashion market affected by Covid-19. This study collected text data with the keyword 'second-hand fashion' from various blogs. We analyzed 24,000 posts before and after the Covid-19 outbreak by applying the LDA algorithm for topic modeling and content analysis. Seven and nine different topics for the period before and after the pandemic respectively were derived. The results revealed that during the pandemic the consumers realized the practical value of sustainability in their daily lives than they did before the pandemic. Furthermore, they tried to minimize transaction anxiety by using diverse platforms with advanced technology. They also realized economic value by buying and selling sneakers in the popular sneakers resale market. The results could help understand the rapidly growing second-hand fashion market during Covid-19.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.5
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• pp.822-838
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• 2023

Reselling, an activity of purchasing high-scarcity products and selling them back at high prices, has gained popularity among those in their 20s and 30s in recent years. This study examines the resell activity process of the MZ generation using the online second-hand platform and its inherent meaning. Interviews with 15 participants in their 20s and 30s showed that respondents have four purchase stages: being influenced by social media, collecting and comparing information using various social media, purchasing efforts, and post-purchase behavior. The research derived three inherent meanings of resell activities: (1) means of self-presentation and differentiation, (2) confirmation of investment skills and aptitude to lead fashion trends, and (3) pleasure of consumption. Respondents indicated meeting self-satisfaction through public selfies on social media. In addition, they emphasized the empirical pleasure during the buying journey by collecting product information, comparing prices, and negotiating with buyers. Our findings confirm the spread of resell activities from minority groups to enthusiastic youth. This study is significant for focusing on fashion products that attract attention in the resell market and examining the respondents' consumption experiences from various perspectives.

• Fashion & Textile Research Journal
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• v.26 no.2
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• pp.166-178
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• 2024

Second-hand trading platforms have emerged as a major transaction method among people, and are particularly quite popular with the MZ Generation (Millennial + Generation Z). These generations are more open to transactions through such platforms. Understanding and analyzing these platforms from the perspective of their primary users can help businesses establish effective marketing strategies and attract new customers. This study examines the effect of second-hand trading platforms on usage intention by dividing the benefits into functional, economic, environmental, social, and hedonic categories for MZ generation consumers who have traded fashion products on such platforms. In addition, it explores how differences in fashion leadership affect the relationship between platform benefits, trust, and attitude. A total of 400 participants were analyzed using IBM SPSS Statistics 26.0 and IBM AMOS 24.0. The results indicate that the benefits of second-hand trading platforms have a significant impact on trust in and attitude toward these platforms. Furthermore, the effect of platform benefits on consumer responses varied based on the extent of fashion leadership. This study provides practical insights for developing marketing strategies for second-hand transaction platforms and underscores the academic significance of studying consumer behavior in a second-hand fashion markets.

• Fashion & Textile Research Journal
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• v.14 no.4
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• pp.544-553
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• 2012

This study examined the influence of consumer self-confidence and self-confidence in fashion coordination on the attitude toward secondhand fashion goods and the purchase intention of secondhand fashion goods. Questionnaire data from 346 university students were analyzed and the results were summarized as follows. First, there were five factor solutions in consumer self-confidence: information acquisition, personal outcomes decision making, social outcomes decision making, consideration-set information, persuasion knowledge. Second, information acquisition, social outcomes decision making, and consideration-set information had significant effects on self-confidence in fashion coordination, while personal outcomes decision making and persuasion knowledge had no effect on self-confidence in fashion coordination. Third, self-confidence in fashion coordination had a significant effect on attitude toward secondhand fashion goods however, it had no effect on purchase intention of secondhand fashion goods. Fourth, attitude toward secondhand fashion goods had a significant effect on the purchase intention of secondhand fashion goods. The results show diverse implications for marketers and managers of secondhand fashion goods.

• Journal of Fashion Business
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• v.28 no.1
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• pp.1-19
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• 2024

This study explores application of upcycling design methods in structural transformation of second-hand denim clothing, aiming to achieve sustainable design objectives. By drawing inspiration from Liu Qing's research methods in the field of circular utilization of denim clothing, this study collected and analyzed cases of structural transformation of used denim clothing from 2020 to 2023. It summarized structural transformation design methods for used denim clothing. Through the development of design works, this study aims to find out the best upgrading and renovation design strategy by applying the method of structural renovation design. This study aims to support the development of a sustainable fashion industry and promote recycling and upcycling of discarded clothing fabrics, thereby reducing resource waste and environmental impact.

• The Research Journal of the Costume Culture
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• v.21 no.3
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• pp.324-337
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• 2013

The purpose of the present study was to investigate the differences in purchase behaviors, buying motives of secondhand clothing and the perception toward secondhand clothing products among the groups as determined by their gender and age. Data were collected by a pilot test and the final questionnaire survey administered to 450 subjects in the age range from 20 to 59, living in Seoul; 430 were used for data analyses. The results showed that 3 factors for buying motives (distinction, affordability, and quality & attractiveness) and 2 factors for perception toward secondhand clothes (positive and negative perceptions) were formulated. Women tended to buy more secondhand clothing products for themselves as well as their family, and put more importance on most of selective criteria than men did. The young were more likely to have negative perception and to buy at diverse places. Those having experiences of buying secondhand clothes showed more positive perception on such products. It is expected that this study provides basic information needed for secondhand apparel companies to develop their marketing strategies to increase customer satisfaction.

• Journal of the Korean Society of Clothing and Textiles
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• v.37 no.4
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• pp.618-630
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• 2013

This study investigates the influence of consumption value on attitude and the repurchase intention of secondhand fashion goods. In addition, this study examines the effect of consumption value on attitudes according to self-confidence in fashion coordination. Questionnaire data from 220 university students who made purchases of secondhand fashion goods were analyzed. The results were as follows. First, there were 5 factor solutions for the consumption value of secondhand fashion goods: rare value, emotional value, functional value, social contribution value, and economic value. Second, rare value, social contribution value and economic value had a positive impact on the attitude toward secondhand fashion goods. Third, attitude had positive impact on the repurchase intention of secondhand fashion goods. Fourth, there was a significant difference in the magnitude of the effect of consumption value on attitude according to self-confidence in fashion coordination. The results of this study provide various guidelines for marketers or retailers who are interested in secondhand fashion goods.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.29-41
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• 2022

Since the first sale of a banner advertisement in 1995, electronic commerce has become a new transaction channel for consumers. With more than 20 years of its history, electronic commerce has become an important consumption channel for everyone and inexperience is no more a reason that discourages the consumption through this channel. The great expansion of this channel is now a formidable thereat to traditional channels. However, products with high asset specificity and complexity are still having difficulty to be traded over the online channel where the experience of the products for a consumer is limited. Especially, variations of the same product's quality depending on how pre-owners used the product and high complexity to describe the quality of the products prevent used goods from being traded over e-channels. Added to that, the information asymmetry between sellers and buyers for used goods makes the establishment of market transaction difficult. Considering the challenges, the current case study discusses thredUP, a clothing resale platform company. In this paper, we study how the company could overcome those limitations in this toughest resale market through the use of AI for dynamic pricing and standarized product quality ratings. In addition, we also hope to provide readers with the opportunity to understand the secondhand industries and its market, and see where it is heading for in the future.