Search Results (738)

As online luxury fashion resale platforms continue to emerge and expand, persistent challenges related to trust and product authenticity have become increasingly pronounced. digital product passports (DPPs) offer a potential solution to these trust-related challenges by providing detailed information about a product, thereby enhancing product transparency and traceability throughout the product lifecycle. Drawing on signaling theory, this study investigates how DPP-enabled platforms influence consumers’ purchase intentions toward luxury fashion resale consumption. An online survey generated 307 valid responses. Structural equation modeling (SEM) was employed to test the proposed hypotheses. A multi-group chi-square difference test was also conducted to test the moderating role of DPP usage experience. The results demonstrate that trust and attitude are decisive predictors of consumers’ intention to purchase second-hand luxury fashion products from DPP-enabled platforms. Risk reduction alone does not directly drive intention, highlighting the distinction between eliminating uncertainty and fostering positive motivation. This study focuses on consumer perception and intention regarding DPPs within the luxury fashion resale market, an area that has received limited empirical attention. By integrating signaling theory with fashion resale and digital innovation, this study offers novel insights into the role of technological transparency in driving consumer engagement in circular fashion. Full article

Xipi lacquer texture generation and interactive product design are important tasks for the digital preservation and creative use of lacquerware cultural heritage. However, existing methods still face limitations in reconstructing process-dependent Xipi lacquer textures and supporting interactive design. These limitations include the difficulty of parameterizing the traditional layering-polishing process, insufficient representation of nonlinear structural features in generated textures, and user fatigue in multidimensional interactive design. Inspired by geographic contour lines, this study proposes a design framework based on Vector Quantized Variational Autoencoder (VQ-VAE) and Interactive Genetic Algorithm (IGA). The framework uses pseudo-contour inputs to guide Xipi lacquer texture generation and integrates the generated textures into a user-guided 3D bracelet evolution process. Experiments on a self-compiled dataset show that the proposed model achieved PSNR $\left(25.2\right)$, SSIM $\left(0.855\right)$, LPIPS $\left(0.285\right)$, and FID $\left(38.2\right)$. User evaluation further showed the performance of the improved IGA in structural stability $\left(4.52\right)$, color exploration $\left(4.38\right)$, evolutionary rhythm $\left(4.65\right)$, innovation retention ($4.25)$, and interaction efficiency $\left(4.42\right)$. The generated assets are further integrated into augmented-reality and virtual fashion-rendering scenarios, indicating the potential applicability of the proposed framework to the digital preservation and interactive design of lacquerware cultural heritage. Full article

Consumer loyalty has become crucial in the sustainable fashion market for continued growth and sustainable competitive advantage. Building upon the theory of loyalty and the Stimulus–Organism–Response (S-O-R) framework, this study investigates how green brand quality, green brand price, and green brand image influence green consumer loyalty. Additionally, this study evaluates the mediating role of green brand trust. Data were collected via an online survey of 340 sustainable fashion consumers. Structural equation modeling (SEM) was used to test direct and mediating hypotheses. The findings reveal that green brand quality and green brand image influenced green consumer loyalty. However, green product price had no effect. Additionally, green brand trust strongly influenced green consumer loyalty. It also played a mediating role between quality, image, and loyalty. Ultimately, this study positions brand image, quality, and trust as foundational mechanisms in sustainable consumer behavior, especially green consumer loyalty. Full article

The fashion and textile industry is undergoing profound transformation driven by regulatory, environmental and societal pressures to reduce its significant contributions to global waste, emissions and resource depletion. In the European Union (EU), this transition is being formalised through the Ecodesign for Sustainable Products Regulation (ESPR), which introduces mandatory sustainability and circularity requirements for textile products, including the Digital Product Passport (DPP). The emerging DPP framework is expected to include product-specific, life-cycle-based environmental information requirements, creating new compliance obligations for garment manufacturers supplying the EU market, particularly those based outside the EU. This study examines the readiness of global garment manufacturers to meet these requirements, with a focus on data availability, supply chain traceability, and alignment with the methodological expectations of the Product Environmental Footprint (PEF) framework. A mixed-methods approach is employed, combining a survey of garment manufacturers in Pakistan, Bangladesh and Turkey with a case study of upcycled garments produced for the Estonian national team for the Paris 2024 Olympic Games. The findings identify key barriers to generating DPP-compliant environmental data, including limited life cycle assessment (LCA) expertise, fragmented and inconsistent upstream datasets, insufficient digital data systems and the practical complexity of applying PEF Category Rules across diverse production contexts. The case study further demonstrates how data gaps constrain the assessment of innovative circular materials, revealing a mismatch between regulatory expectations and current industry capabilities. Overall, this study highlights the need for phased DPP implementation, simplified cradle-to-gate assessment approaches and clearer, more harmonised methodological guidance to support an achievable and equitable transition towards sustainable textile supply chains. Full article

The growing emphasis on sustainability in fashion and textile systems has renewed interest in natural dyes as both ecological colorants and expressive design tools. This study investigates a design-oriented approach to sustainable screen-printing by combining plant-based dyestuffs with conceptual pattern development and scientific performance analysis. It assumes that natural dyes can function not only as environmentally responsible alternatives to synthetic colorants but also as active design materials within contemporary textile printing. Accordingly, the study asks how dye type and fiber type influence color performance, fastness behavior, and fiber–dye interaction in screen-printed natural fabrics. Natural dyes derived from Rubia cordifolia (Rubia^®), Punica granatum peel (Mallow^®), and Morus alba leaves (Leafy Green^®) were applied to 100% cotton, linen, and silk fabrics through an environmentally responsible screen-printing process. A garlic-inspired motif was developed to support the study’s visual and conceptual framework by representing circularity, low-impact agriculture, and cultural sustainability. Colorimetric properties (L*, a*, b*, K/S, ΔE) were measured by spectrophotometric analysis, while washing and rubbing fastness were evaluated according to international standards. FTIR spectroscopy was used to examine fiber–dye interaction mechanisms, and statistical significance was tested through two-way ANOVA. The findings show that fabric type is the dominant factor affecting color performance, with cotton exhibiting the highest color strength due to its cellulose-rich and hydroxyl-dense structure. Rubia^® produced the darkest and most saturated tones, whereas Mallow^® yielded lighter pastel-like shades. FTIR results indicated that dye fixation occurred primarily through non-covalent interactions, explaining the balance between aesthetic richness and moderate fastness. The study offers a replicable model for environmentally responsible, design-oriented textile production that integrates material innovation with cultural and visual narratives. Full article

Intermittent sales patterns, prevalent in fast-fashion retail, pose a critical challenge for conventional forecasting methods. This study empirically compares one-stage and two-stage machine learning (ML) frameworks with classical benchmarks (Croston, SBA). The two-stage approach uses a Random Forest classifier for demand occurrence, followed by regression models (RF, GBM, XGBoost, LightGBM) for magnitude. Models are evaluated using weekly sales data from an Iraqi fashion retailer, incorporating rich exogenous features like product attributes, pricing, weather, and special events across 64 unique attribute-defined product group time series. Performance is assessed via a fixed 13-week holdout and rolling-origin cross-validation, with LSTM and Temporal Fusion Transformer (TFT) serving as deep learning benchmarks. Empirical findings show that machine learning configurations achieve superior WRMSSE accuracy, with two-stage models often outperforming one-stage counterparts, and both significantly surpassing classical and deep learning baselines. The Two-Stage XGBoost yielded the lowest WRMSSE, establishing the feature-engineered two-stage framework as the strongest overall for this intermittent retail setting. Furthermore, a detailed SHAP analysis elucidated the distinct feature contributions to demand occurrence versus demand magnitude, providing actionable insights for inventory management. This rigorous benchmarking analysis offers practical implications for inventory planning and demand management in volatile markets, highlighting the effectiveness of explicit demand occurrence modeling. Full article

Perishable products are usually priced in real-time to volatile market environments, thereby optimizing inventory control, minimizing resource wastage, and maximizing corporate profitability. Based on the public dataset from the 2023 Higher Education Press Cup National College Students Mathematical Modeling Competition, this paper addresses the challenge of multi-product joint pricing for perishable fresh produce and proposes an attention-augmented proximal policy optimization algorithm (termed ATT-PPO), which embeds an attention mechanism into the proximal policy optimization (PPO) framework. The integrated attention mechanism confers three core advantages to the model: first, it dynamically captures inter-product interdependencies, enabling an accurate reflection of cross-price elasticity and demand correlations; second, it reduces feature redundancy and computational overhead in multi-product collaborative pricing strategies; third, it enhances both the interpretability and computational efficiency of the model. Experimental results demonstrate that in the scenario of multi-product pricing, the ATT-PPO algorithm achieves competitive performance compared to PPO, DDPG (Deep Deterministic Policy Gradient), SAC (Soft Actor-Critic), and TD3 (Twin Delayed Deep Deterministic Policy Gradient), with the key advantage lying in its ability to provide interpretable attention weights that reveal dynamic cross-product dependencies in pricing decisions. This study not only expands the applicability of DRL (Deep Reinforcement Learning) to practical economic problems in the fresh produce sector but also provides valuable theoretical insights that can be generalized to other short-lifecycle product domains, including fashion apparel and consumer electronics. Full article

The fashion industry generates a major environmental impact, requiring integrated sustainable approaches. This study integrates six thematic axes—sustainability, modular design, natural materials, eco-friendly dyeing, multidimensional comfort and consumer perception, and radial composition—into an integrative framework for sustainable design. The mixed-methods methodology comprises four stages: (I) a quantitative stage (questionnaire, n = 150); (II) an experimental stage (testing of comfort characteristics of linen fabrics according to ISO standards, and indigo dyeing through three techniques: uniform, tie-dye, and shibori); (III) a digital design stage in CLO3D and physical fabrication of the prototype; (IV) a prototype testing and validation stage (panel, n = 20). The prototype provides functional adaptability through 8 design configurations, versatility through reversibility, and aesthetic diversity through the radial composition, yielding 16 distinct wearing modes within a single product. Panel evaluation confirms high prototype acceptance (M = 4.81–4.95), and physical interaction with the prototype significantly increases purchase intention compared with conceptual evaluation (M_pre = 3.54; M_post = 4.60; d = 2.04; p < 0.001). The contribution validates a framework that integrates six dimensions of sustainable fashion into a coherent clothing design model, demonstrating design’s role as a practical instrument in the sustainability transition, with applied implications for designers and researchers. Full article

Female fashion models face intense bodily surveillance within a competitive and largely unregulated industry. While many young recruits endure the industry’s initial demands, less is known about how these formative experiences are later interpreted. Grounded in feminist and phenomenological perspectives, this article presents an inductive analysis of 18 semi-structured interviews with female models aged 25+, exploring entry into modelling, socialization into industry norms, and longer-term effects on body image, eating attitudes, and embodied practices. Five interconnected themes were identified: growing up “superfast”; learning to eat less; being treated as a product; boundary violations as a darker side of modelling; and building resilience within a callous industry. Early immersion in modelling culture shaped psychological development, with self-worth becoming closely tied to conformity with a narrowly defined thin ideal. Aesthetic labour extended beyond paid work to continuous bodily regulation and self-surveillance, producing a persistent tension between the lived, sensing body (Leib) and the body as an object for evaluation (Körper). Disordered eating emerged as a normalised employment strategy. While maturity could soften this process, participants described ongoing attempts to reconcile bodily needs with external judgements. The fashion industry thus emerges as a concentrated site of objectification, with enduring consequences for embodied wellbeing. Full article

There is renewed interest in local sourcing, regional supply chains, and the rebuilding of fiber-to-fashion systems. However, limited attention has been paid to the upstream role of fiber farmers and the infrastructure that enables or constrains regional textile economies. This study investigates the opportunities and challenges of fiber farming in West Virginia and explores the motivations that drive participation in this sector. Using a qualitative approach, semi-structured interviews were conducted with 16 fiber farmers across West Virginia. The findings revealed five interconnected themes: heterogeneous actants, the translation of wool, regional network breakdown, festivals and social media as network hubs, and institutional gaps and network fragility. The results indicate that fiber farming persists through strong community networks, adaptive entrepreneurial strategies, and deep attachments to place. However, its economic viability is constrained by declining processing infrastructure, labor shortages, weakened institutional support, and fragmented supply chains. These challenges also have important sustainability implications. Most notably, wool is often discarded because processing and transportation costs exceed its market value, resulting in the waste of a renewable and biodegradable fiber that could otherwise remain in productive use. This study contributes to the literature on local sourcing, rural entrepreneurship, and sustainable and circular economies by highlighting the relational infrastructures required to rebuild regionally embedded textile systems in Appalachia and beyond. Full article

To achieve personalized garment production based on a three-dimensional (3D) point cloud, a garment pattern generation framework using surface flattening is proposed. 3D point cloud data of 190 subjects were preprocessed to achieve 17 dimensions by automatically locating five landmarks, including side neck point, front neck point, shoulder point, bust point, and waist point, by using the maximum distance method. 2D initial patterns were generated from processed point cloud data through structural line design and surface flattening. In total, 145 standardized garment patterns were justified according to the correction rules of a Japanese Bunka-Style Bodice Block to conform to standard structures. A 2D coordinate system containing 23 feature points, three auxiliary lines, and seven auxiliary points was established for pattern measurement. Finally, personalized pattern generation rules were determined by backward stepwise regression analysis between body measurements and pattern parameters. The results show that the mean error of five landmarks is below 2.49 mm, validating the accuracy of 3D point cloud-based automatic landmark localization, and the generated pattern errors of five key parameters meet standard tolerances. Meanwhile, virtual fitting effects of the generated patterns are satisfactory with low and evenly distributed pressure. The proposed garment pattern generation method meets personalized garment fit requirements and provides a feasible technical path for garment production in the fashion industry. Full article

The fashion industry generates significant environmental impact through overproduction and the short life cycles of clothing products. Modular design, which allows multiple wearing configurations from a single product through removable and interchangeable components, represents a promising sustainable alternative but lacks standardized methodologies that integrate digital innovation with physical production. This study develops and validates an integrated methodology for creating versatile modular clothing products. Based on the three-dimensional framework of modularity (structure, function, and system), four categories of modular elements were defined and organized in a CLO3D (Version 2026.0.202; CLO Virtual Fashion Inc., Seoul, Republic of Korea) digital library. Combinatorial calculation generated 360 theoretical variants, of which 24 were selected as structurally and aesthetically feasible. A physical prototype consisting of a vest, four modules and three sleeve variants was made from 100% linen fabrics (290 and 180 gsm) with snap fastener tape and natural shell buttons. The digital–physical visual comparison confirmed high concordance for proportions and alignment of the modules, with limitations in simulating the fabric drape. The 24 validated configurations demonstrate that a single modular clothing product can function as an effective wardrobe multiplier. The study confirms that integrating the CLO3D digital library with physical prototyping from sustainable materials constitutes a viable and replicable methodology in the fashion industry. Full article

The objectives of this study are to examine the direct relationships among perceived ethics, perceived sustainability, customer trust, customer engagement, and customer loyalty; and to investigate the mediating roles of customer trust and customer engagement in explaining the relationship between ethical and sustainability perceptions and customer loyalty. Using the Stimulus–Organism–Response (SOR) framework and the Theory of Planned Behavior (TPB) as theoretical foundations, this research examines how ethical and sustainability perceptions within social commerce environments influence customers’ psychological states and behavioral responses. A quantitative approach was used, involving data collection from 360 Thai consumers who had previously bought sustainable fashion items through social media. The proposed model was then evaluated using partial least squares structural equation modeling (PLS-SEM). The results suggest that consumers’ evaluations of seller ethics significantly enhance their perceptions of product sustainability, customer trust, and engagement. Furthermore, perceived sustainability of fashion products affects both trust and engagement. Customer trust subsequently promotes both engagement and loyalty; however, customer engagement exhibits the most substantial direct effect on customer loyalty. Mediation analysis confirms the essential functions of trust and engagement in mediating the impacts of ethical and sustainability perceptions on loyalty. These findings highlight the importance of ethical transparency and proactive customer engagement in fostering trust and long-term customer loyalty within social media-based sustainable fashion commerce. Therefore. This study provides both theoretical and practical insights for sustainable fashion enterprises functioning within digital contexts. Full article

This study investigates how externally designable attributes of eco-printed womenswear shape consumer acceptance. Existing research has paid more attention to sustainability attitudes in general than to how product-specific design cues influence acceptance in this context. Using an exploratory sequential mixed-methods design, the study combines qualitative interviews with a survey of 992 female consumers in mainland China. The results show that consumer acceptance develops through an attribute–value–attitude–intention pathway rather than from abstract environmental concern alone. Fabric Perception, Colour Preference, and Structure and Craft Awareness influence functional value, emotional value, and environmental value, which subsequently shape consumer attitude and purchase intention. Among these attributes, Structure and Craft Awareness exerts the strongest effect on environmental value and consumer attitude. The study further develops a data-calibrated analytic hierarchy process (DC-AHP) to translate behavioural evidence into design priorities. The findings extend sustainable fashion research by clarifying the product-based mechanism of consumer acceptance and provide evidence to support design-priority setting in eco-printed womenswear. Full article

This article offers an exploratory overview of the contemporary Ethiopian textile, fashion and apparel system. The contribution originated from a teaching experience in Addis Ababa within the framework of the AICS–UNIDO-funded project “Ethiopia: Support to Youth and Women through Products and Services Development and Public–Private Partnerships in the Fashion Value Chain” which prompted the authors to deepen their understanding of the local fashion ecosystem. Drawing on informal conversations, observations, and ethnographically oriented field notes, the authors developed the analysis through desk research and a review of the relevant literature. The picture that emerges reveals both the creativity and strong entrepreneurial drive of Ethiopian designers, alongside the structural barriers they commonly face, including limited access to materials, investment, and institutional support. Designers are shown to negotiate ongoing tensions between cultural heritage and global aesthetics, while also contending with local consumption patterns situated between second-hand clothing markets and international brands. These dynamics highlight both the challenges and the potential of the Ethiopian fashion scene, pointing to opportunities for mutual learning and for fostering fashion practices that are sustainable, globally relevant, and firmly grounded in local contexts. Full article