Journal of the Korean Society of Clothing and Textiles
Journal of the Korean Society of Clothing and Textiles is the official publication of The Korean Society of Clothing and Textiles. It was launched in 1977. Journal of Korean Society of Clothing and Textiles aims at providing up-to-date research contents and news on cutting-edge technologies, as well as facilitating the interaction between academia worldwide and related industries, thereby enhancing the professional expertise of its members and contributing to the advancement of apparel.
• Frequency : issued six times a year
• ISSN : 1225-1151 (Print)/2234-0793 (Online)
• Year of Launching : 1977
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The Influence of Design Entity (Human vs. AI) on Fashion Product Purchase -The Mediating Effects of Authenticity and Curiosity- 패션 제품 구매에 대한 디자인 주체(인간 vs. AI)의 영향 -진정성과 호기심의 매개효과를 중심으로-
The Influence of Design Entity (Human vs. AI) on Fashion Product Purchase -The Mediating Effects of Authenticity and Curiosity- 패션 제품 구매에 대한 디자인 주체(인간 vs. AI)의 영향 -진정성과 호기심의 매개효과를 중심으로-
This research investigates how the design entity of fashion products―human designers versus artificial intelligence (AI)―shapes consumer responses. It also clarifies the psychological mechanisms underlying consumer responses to AI-driven fashion design, emphasizing the mediating roles of perceived authenticity and curiosity, along with the moderating role of emotional trust in AI. An experimental study with a between-subjects design was conducted using a hoodie featuring AI-generated graphics. Participants were recruited from an online consumer panel in China via PowerCX and were randomly assigned to the human or AI design entity condition. Data were analyzed using the SPSS Process Macro. Results indicate that human-design entity increases purchase intention through a sequential mediation of authenticity and curiosity, whereas the AI-design entity primarily enhances purchase intention through curiosity. Moreover, emotional trust in AI technology influences these relationships. Specifically, when emotional trust is low, authenticity increases purchase intention and substantially stimulates curiosity, which further enhances purchase intention. These findings highlight the importance to developing marketing strategies tailored to the design entity. Fashion brands can enhance their marketing by highlighting the curiosity sparked by AI-generated designs.
Key Words
패션 디자인 주체, AI 생성형 디자인, 진정성, 호기심, AI 기술에 대한 감정적 신뢰, Fashion design entity, AI-generated design, Authenticity, Curiosity, Emotional trust in AI technology
The Effects of Ad Exposure Type and Self-Construal on Consumer Attention and Environmental Behavioral Intention in Fashion CSR Advertising 광고 노출 유형과 자기 해석 수준이 패션 CSR 광고에서 소비자 주의집중과 환경행동 의도에 미치는 영향
공흠우 Heumwoo Kong , 최동은 Dongeun Choi , 김세은 Seeun Kim
The Effects of Ad Exposure Type and Self-Construal on Consumer Attention and Environmental Behavioral Intention in Fashion CSR Advertising 광고 노출 유형과 자기 해석 수준이 패션 CSR 광고에서 소비자 주의집중과 환경행동 의도에 미치는 영향
공흠우 Heumwoo Kong , 최동은 Dongeun Choi , 김세은 Seeun Kim
This study investigates the effects of ad exposure type (directed vs. incidental) and self-construal (self-oriented vs. other-oriented) on consumer attention and environmental behavioral intention, drawing on construal level theory. Data were collected through an online survey of 338 participants in their 20s and 30s in the Seoul metropolitan area. Reliability analysis, t-tests, two-way analysis of variance, and moderated mediation analysis were performed using SPSS 25 to examine the mediating role of consumer attention. The interaction between ad exposure type and self-construal significantly influenced consumer attention and environmental behavioral intention. Specifically, consumers with a self-oriented construal processed CSR ads more concretely and responded strongly under directed exposure. Conversely, those with an other-oriented construal interpreted ads in a more abstract and value-based manner, showing greater environmental intention even under incidental exposure. Consumer attention significantly mediated the interactive effect of ad exposure type and self-construal on environmental behavior intention, confirming attention as an important cognitive mechanism in CSR advertising effectiveness. This study contributes to the literature by demonstrating that consumer responses to CSR advertising vary according to the interaction between self-construal and ad exposure type. It provides practical implications for developing effective and sustainable communication strategies in the fashion industry.
Key Words
CSR advertising, Self-construal, Ad exposure, Consumer attention, Environmental behavioral intention, CSR 광고, 자기 해석, 광고 노출, 소비자 주의집중, 환경행동 의도
From Sustainability Values to Consumer-Interpretable Signals -Constructing Authenticity in Sustainable Fashion Brands-
Haejin Choi , Youngho Shim , Sae Eun Lee , Yuri Lee
This study investigates the structural gap between sustainable fashion entrepreneurs’ ethical signaling and consumers’ market-based interpretation, conceptualized as the value translation gap. Drawing on interviews with five sustainable fashion founders and focus groups with 16 consumers, we examine how sustainability meanings are reframed and interpreted across brand-consumer signaling systems. Means-end chain mapping shows that entrepreneurs often communicate sustainability cautiously to preserve authenticity, whereas consumers evaluate authenticity through a clear brand vision, credible evidence of concrete actions, consistency, and market-legible cues rather than broad sustainability claims. Consumers’ fatigue with sustainability messaging does not reflect rejection of sustainability itself but dissatisfaction with messages that lack credibility and interpretability. We advance sustainability communication by theorizing signal reframing as a mechanism for translating ethical commitments into market-legible signals. Extending signaling theory, we demonstrate that successful value translation depends not on the strength of ethical appeals but on how consumers interpret and construct meaning from sustainability signals. These findings highlight the need to reconfigure sustainability narratives into clear, credible, and interpretable signal systems aligned with consumers’ evaluation criteria.
Key Words
Authenticity decoding, Signal reframing, Sustainability claim fatigue, Sustainable fashion entrepreneurs, Value translation gap
Category-Specific Consumer Perceptions of Cooling Functional Apparel -Insights from Text Mining of Online Reviews- 냉감 기능성 의류의 제품군별 소비자 인식 분석 -온라인 리뷰 텍스트마이닝을 중심으로-
Category-Specific Consumer Perceptions of Cooling Functional Apparel -Insights from Text Mining of Online Reviews- 냉감 기능성 의류의 제품군별 소비자 인식 분석 -온라인 리뷰 텍스트마이닝을 중심으로-
Despite increasing demand for apparel with cooling functions, how consumer perceptions of cooling-related comfort differ by product category remains unclear. This study explored category-specific consumer perceptions and evaluation criteria by analyzing online reviews of apparel marketed with cooling functions. Long pants, T-shirts, and bras were selected because they are worn on different body areas and require distinct functions. For each category, 600 reviews were web-crawled using Python from each of the two most-reviewed products on Musinsa, yielding 3,600 reviews in total. Frequency, TF-IDF, N-gram, and ego-network analyses were conducted using Textom. Pants reviews emphasized immediate coolness, with “cool” and “thin” strongly associated with breathability and movement comfort, while mentions of “rustling” suggested that fabric noise can cause discomfort. T-shirt reviews highlighted fit and the sheerness of thin fabrics, with “sheerness” being a common complaint. Bra reviews focused on tactile comfort and components such as straps, where thin straps were valued for lightness but occasionally associated with inadequate support. Although “cool” emerged as a common keyword across all categories, the factors associated with satisfaction differed. These findings demonstrate that perceived coolness is constructed differently according to body area and garment structure, highlighting the need for category-specific priorities in functional apparel planning.
Key Words
Cooling functional apparel, Consumer perceptions, Product category, Online reviews, Text mining, 냉감 기능성 의류, 소비자 인식, 제품군, 온라인 리뷰, 텍스트마이닝
Development of 3D-Printed Textiles Through the Reinterpretation of Traditional Embroidery Techniques Based on Fused Deposition Modeling Technology 자수 기법을 활용한 3D 프린팅 텍스타일 개발
장루요 Luyao Zhang , 이지원 Jiwon Lee , 전재훈 Jaehoon Chun
Development of 3D-Printed Textiles Through the Reinterpretation of Traditional Embroidery Techniques Based on Fused Deposition Modeling Technology 자수 기법을 활용한 3D 프린팅 텍스타일 개발
장루요 Luyao Zhang , 이지원 Jiwon Lee , 전재훈 Jaehoon Chun
This study explores the development of 3D-printed textiles by reinterpreting traditional embroidery techniques using fused deposition modeling (FDM) technology. It aims to transform the aesthetic and structural principles of traditional embroidery into digital additive manufacturing parameters, demonstrating a sustainable production method for the contemporary fashion industry. Seven representative embroidery techniques―tulle, ribbon, cord, beads, spangle, cutwork, and appliqué―were selected based on classification frameworks and frequency analysis of contemporary market cases. They were categorized into three formative principles― point, line, and plane―and systematically mapped to corresponding FDM design variables, including layer thickness, layer count, density, curvature, and nozzle paths. In two phases of experimental sampling, the technical feasibility of each technique on base fabrics was first confirmed. The second phase emphasized the structural optimization and aesthetic enhancement of tulle and ribbon embroidery. These were selected for their design variable adjustability, structural improvability, and process repeatability, alongside their compatibility with FDM’s path-based extrusion process. The significance of this research lies in expanding 3D-printed textile studies beyond the fabric-adhesion focus of previous studies toward reproducing the formative qualities of embroidery. It establishes a technical framework and foundational guidelines for the artistic and functional expansion of 3D printing in fashion design.
Key Words
3D printing, 3D-printed embroidery techniques, 3D-printed textiles, Additive manufacturing, 3D 프린팅, 3D 프린팅 자수 기법, 3D 프린팅 텍스타일, 적층 제조
Consumers’ Continuous Intention to Use Laundry O2O Services -The Role of Trust According to the Value-Based Adoption Model- 세탁 O2O 서비스에서 소비자의 지속이용의도 형성 메커니즘 -가치기반수용모델과 신뢰의 역할-
금민정 Minjeong Geum , 추호정 Ho Jung Choo , 김태연 Taeyoen Kim
Consumers’ Continuous Intention to Use Laundry O2O Services -The Role of Trust According to the Value-Based Adoption Model- 세탁 O2O 서비스에서 소비자의 지속이용의도 형성 메커니즘 -가치기반수용모델과 신뢰의 역할-
금민정 Minjeong Geum , 추호정 Ho Jung Choo , 김태연 Taeyoen Kim
Online-to-offline (O2O) platforms integrate online ordering with offline service delivery, reshaping traditional service industries. Recently, laundry O2O services have emerged as a fast-growing sector that offers convenient pickup and delivery through mobile applications. However, unlike many other digital services, these require consumers to entrust personal clothing items to service providers, potentially increasing uncertainty and perceived risks. This study examines the structural mechanism underlying consumers’ continuous intention to use laundry O2O services. Drawing on the value-based adoption model (VAM), the study incorporates trust to better explain consumer decision-making in this context. A research model including service utility, perceived risk (privacy risk and quality risk), trust, perceived value, and continuous intention to use was developed and tested using survey data. The results showed that service utility significantly increased perceived value, while perceived value positively influenced continuous intention to use. Privacy risk did not significantly affect perceived value, whereas quality risk showed a significant effect, contrary to the hypothesized direction. In contrast, trust showed strong positive effects on both perceived value and continuous intention to use. These findings suggest that consumers may rely on trust-based judgments in addition to calculative value assessments in experience-based platform services such as laundry O2O services.
This study investigates how individuals’ perceived creativity in AI-assisted fashion design activities influences behavioral engagement, specifically sharing, learning, and endorsing behaviors. Participants were instructed to use a generative image AI system to design a T-shirt graphic and subsequently evaluated their design outcomes and overall experience with the AI design activity. A total of 200 valid responses were collected and analyzed using descriptive statistics, confirmatory factor analysis, and structural equation modeling. The results indicated that perceived creativity is a multidimensional construct comprising originality, relevance, and artistry. Among these dimensions, perceived originality and perceived relevance positively impacted sharing behavior but not learning engagement, whereas perceived artistry positively impacted both sharing and learning behaviors. Furthermore, both sharing and learning behaviors positively influenced endorsing behavior. The findings demonstrate that not all dimensions of perceived creativity contribute equally to behavioral engagement in AI-assisted design contexts. By distinguishing the differential effects of creativity dimensions, this study offers theoretical insights into consumer engagement in human-AI co-creation as well as practical implications for designing AI-supported creative systems that foster meaningful user participation and advocacy.
Key Words
AI-assisted design, Perceived creativity, Behavioral engagement, AI 보조 디자인, 창의성 지각, 행동적 인게이지먼트
Predicting Review Helpfulness in Online Cosmetic and Personal Care Shopping -A Machine Learning Approach-
Cosmetic and personal-care products are archetypal experience goods. Their qualities―skin compatibility, olfactory profile, texture, and efficacy―cannot be fully assessed before purchase, driving consumers toward peer-generated reviews. However, review volume complicates the identification of useful content and can decrease the marginal value of individual reviews. Using a one-million-review stratified sample from Amazon, this study develops a machine-learning framework to predict review helpfulness at posting and identifies the most influential features. Three findings are noted. First, post-hoc SHapley Additive exPlanations analysis documents a nonlinear concreteness threshold near a Brysbaert score of 2.3-2.5: reviews below this threshold show a significant negative model-implied helpfulness contribution, consistent with Elaboration Likelihood Model central-route limits. Second, negative predictive contributions of aggregate ratings and review volume act as a crowding-out (substitution) mechanism, displacing individual reviews rather than causing cognitive overload. Third, within-category retraining reveals heterogeneous feature emphases. Namely, the analysis reveals a strong predictive reliance on scent-related semantic descriptors in fragrance and divergent roles for image presence. These findings have implications for review curation by category and the design of reviewer guidance.
Taxonomy-Driven Ontology for Modeling Fashion Consumer Cognitive Structures -Enhancing Recommendation Search Based on Consumer Values, Situations, and Constraints- 패션 소비자의 인지 구조 모델링을 통한 가치 및 상황 기반 추천 검색의 고도화 -텍사노미 기반 온톨로지 구축을 중심으로-
Taxonomy-Driven Ontology for Modeling Fashion Consumer Cognitive Structures -Enhancing Recommendation Search Based on Consumer Values, Situations, and Constraints- 패션 소비자의 인지 구조 모델링을 통한 가치 및 상황 기반 추천 검색의 고도화 -텍사노미 기반 온톨로지 구축을 중심으로-
Bridging the semantic gap between abstract consumer intent and concrete product attributes remains a critical challenge in fashion e-commerce. Grounded in means-end chain and schema theories, this study develops a taxonomy-based ontology to model consumers’ multilayered cognitive structures. The methodology involves a two-stage technical workflow: first, in-depth interviews with 41 high-involvement female fashion majors were conducted to identify cognitive nodes across situational triggers, psychological values, and physical constraints. Second, these insights were formalized into a semantic knowledge graph using a rule-based inference framework, incorporating binary activation properties and Boolean logic. According to the results, fashion decision- making follows a context-driven inference structure where situational factors trigger specific values, subsequently mapped to attributes through semantic links such as “isTriggeredTo” and “isRealizedBy.” Notably, the model can support a dynamic filtering mechanism where body-related constraints (e.g., inhibitory conditions) prune incompatible product nodes and induce alternative selections. By transforming these relationships into a multi-stage semantic inference process, the proposed framework demonstrates how natural language input can be translated into precise, attribute-level recommendations. This research provides a computationally structured knowledge graph for intelligent conversational commerce, offering a scalable technical solution that aligns digital platforms with fashion consumption’s complex, multidimensional nature.
Key Words
Fashion ontology, Fashion search recommendation, Cognitive decision-making, Intelligent inference, Fashion taxonomy, 패션 온톨로지, 패션 검색 추천, 인지적 의사결정, 지능형 추론, 패션 텍사노미
Fashion Experiences Through Remediated Fashion Shows -Focusing on YouTube Content Analysis-
This study examines how fashion show experiences are transformed when fashion shows are remediated through social media. Drawing on remediation theory, it analyzes social media fashion shows as differently remediated formats and examines how users perceive and experience these formats through YouTube comments. The study addresses three research questions: (1) What keyword patterns and discourse structures appear in user comments on social media fashion shows? (2) How do these discourse structures differ according to remediated fashion show formats? (3) How do these differences reveal users’ mediated fashion experiences afforded by social media fashion show? This research adopted a quantitative method, namely, text mining analysis. Social media fashion shows were divided into immediacy and hypermediacy fashion shows. Text mining analysis of YouTube comments identified major keyword patterns and discourse structures according to fashion show type. Then, a comparative analysis of the frequency of keywords and concepts by fashion show type indicated that differences in fashion experiences were due to formal changes to fashion shows brought about by social media. These findings reveal how technological advances in fashion media are transforming one’s experience of fashion.
Key Words
Social media, Remediation, Fashion experience, Fashion shows, Social big data
Building Trust in Recommerce -How Seller Information Fosters Cognitive and Affective Trust to Drive Purchase Intention-
This study investigates how sellers’ information characteristics, including transparency and richness, influence consumers’ trust formation and purchase intention on recommerce platforms, using the stimulus-organism- response framework to understand circular fashion practices. Data were collected from 395 adults, aged 20- 39, with recent experience on recommerce platforms through online surveys. Structural equation modeling was used to test the relationships among information transparency, information richness, cognitive trust, affective trust, and purchase intention. Furthermore, multi-group analysis examined the moderating effect of sustainability awareness. Information transparency significantly influenced cognitive trust, while information richness affected both cognitive and affective trust. Cognitive trust influenced affective trust, which in turn directly affected purchase intention, indicating a sequential mediation mechanism. Sustainability awareness moderated these relationships, making the effect of information transparency on cognitive trust significant only for consumers with high sustainability awareness. Cognitive trust must pass through affective trust to influence purchase behavior in recommerce environments. Unlike in traditional e-commerce, cognitive evaluations alone are insufficient for purchase decisions in secondhand trading environments. The findings enhance circular economy literature by demonstrating how sustainability values moderate information processing mechanisms, providing a theoretical foundation for understanding consumer behavior on sustainable commerce platforms.
Key Words
Circular economy, Recommerce platform, Information transparency, Information richness, Cognitive and affective trust
An Analysis of Project Descriptions and Consumer Comments in Fashion Hanbok Crowdfunding Projects 크라우드펀딩 패션한복 프로젝트의 소개글과 소비자 댓글 분석
This study analyzed project descriptions and consumer comments from 404 successful fashion hanbok crowdfunding projects on the Tumblbug platform, focusing on how evaluation values are constructed in both creators’ messages and consumers’ responses. Morphological and frequency analyses were conducted using Python-based natural language processing and co-occurrence network analysis. Sentiment analysis was performed on 2,883 consumer comments using the KNU Korean Sentiment Dictionary and KcBERT model. Key findings are as follows. First, project descriptions revealed that creators pursued a strategy of recontextualizing tradition in modern lifestyles, centering on concepts of “modern” and “daily wear,” with fabric and design as core network nodes. Second, consumer comments indicated that aesthetics served as the main evaluation criterion, followed by size, fabric, and quality as primary satisfaction factors. Third, sentiment analysis showed an overall positive orientation, highlighting beauty and color in positive comments, while size and fabric issues were noted negatively. Fourth, finishing details recorded the highest negative response rate, highlighting the need for improved quality control. This study confirms a dual structure between creator messaging and consumer evaluation, suggesting that enhancing fit information, fabric quality, complete styling proposals, and finishing management is essential for improving consumer satisfaction.
Key Words
Fashion hanbok, Crowdfunding, Text mining, Co-occurrence network analysis, Sentiment analysis, 패션한복, 크라우드펀딩, 텍스트 마이닝, 공출현 네트워크 분석, 감성 분석
Anthropometric Indicators and a Body Classification System for Elderly Women 노년 여성의 체형 분류를 위한 지표 및 체계 제안
최지영 Jiyoung Choi , 김예은 Ye Eun Kim , 최희은 Hee Eun Choi
This study aimed to identify anthropometric indicators of body composition characteristics and propose a body classification system for elderly women. Anthropometric data from 249 Korean women aged 70-84 years were obtained from the 8th Size Korea survey and corresponding InBody measurements. Conventional obesity indices and anthropometric shape ratio variables were analyzed for their associations with fat mass and skeletal muscle mass. The results indicated strong associations between body mass index (BMI), Röhrer index, and Vervaeck index with body fat mass and visceral fat level. Conversely, skeletal muscle mass showed relatively weak associations with these conventional obesity indices. Among the anthropometric variables, the calf circumference- to-height ratio showed the strongest association with skeletal muscle mass. Factor analysis identified two primary morphological dimensions: lower-body and trunk structures. Significant differences in wholebody morphological characteristics were observed among groups classified by the calf circumference-to-height ratio. Accordingly, a body classification system combining BMI and the calf circumference-to-height ratio was proposed. BMI indicated fat-related body composition characteristics, whereas the calf circumference-to-height ratio represented body shape characteristics associated with skeletal muscle mass. Overall, the proposed system demonstrates the potential of anthropometric measurements for classifying body shape characteristics linked to body composition in elderly women.
Key Words
Elderly women’s body shape, Body mass index, Calf circumference-to-height ratio, Anthropometric indicators, Body shape classification, 노년 여성 체형, 체질량지수, 장딴지둘레-신장비, 인체측정 지표, 체형 분류
