Search Results (680)

Sustainable consumption is central to sustainable development goals (SDGs), yet research on consumer behavior (CB) remains scattered. Studies on green consumption, digital retail, fashion, food systems, digital finance, energy, and tourism have developed largely in isolation, and few studies have investigated what these settings share or how sustainability-relevant behavior unfolds after the moment of purchase. This study takes a wider view, applying the SPAR-4-SLR protocol to a decade of CB and sustainability scholarship and combining machine-learning-based BERTopic thematic modeling with SDG mapping, organized through a Theory–Context–Method and Antecedents–Decision–Outcome (TCM–ADO) lens. Seven themes emerged, concentrated on SDGs 8 (decent work), 9 (industry innovation), and 12 (sustainable consumption). Together, they point to a shift away from individual purchase choices toward consumption that is multistage, digitally mediated, and institutionally embedded. Across the seven theme-level summaries, trust, engagement, risk perception, ethics, literacy, and experience appear repeatedly. Because several of these constructs were included in the retrieval query, this pattern is interpreted as cross-theme recurrence within the query-defined corpus rather than as independent evidence of universal prevalence across sustainable consumer-behavior research. Digital and platform mediation appears as one cross-cutting condition, and is most visible where consumption is heavily platform-based. On this basis, the review proposes a process framework that treats antecedents as capability, vulnerability, and layered trust; decisions as multistage and mediated; and outcomes as interdependent SDG bundles. Twelve propositions and a research agenda follow, testable across food, energy, finance, fashion, tourism, and digital retail. Full article

Fashion trend forecasting is crucial for proactive supply chain management, sustainable production, and personalized marketing. However, accurately predicting fine-grained fashion trends across diverse user groups remains challenging, as conventional numerical models rely solely on historical popularity signals and cannot explicitly exploit the high-level semantic context underlying trend evolution. To address this limitation, we propose a Dual-Stream Driven Fashion Trend Forecasting (DDFTF) framework that integrates numerical forecasting with textual semantic reasoning. The numerical stream employs a multi-scale patch Transformer with metadata-aware feature fusion to capture temporal dynamics, while the semantic stream converts historical trends into structured textual descriptions, extracting interpretable semantic representations of global trends and turning points. A residual fusion module combines both streams by treating semantic signals as complementary corrections to numerical predictions. Extensive experiments on the FIT and GeoStyle benchmarks demonstrate that DDFTF consistently outperforms state-of-the-art methods, achieving up to a 14.6% relative MAE reduction in long-term forecasting. Ablation and qualitative analyses further show that the performance gains arise from meaningful semantic information rather than increased model capacity, while also improving the interpretability of fashion trend prediction. Our code is publicly available. Full article

RFID is usually used for product recognition, object-level tracking, inventory visibility, logistics monitoring, authentication, and automated data capture for various supply chain industries. RFID can enable traceability, authentication (anti-counterfeiting), order allocation, inventory control, warehouse efficiency, logistics monitoring, safety management and sustainability information in apparel, fashion, and product-based supply chains. The current evidence, however, is quite diverse, ranging from fashion supply chains and manufacturing analytics to inventory systems, logistics, asset tracking, environmental monitoring, worker safety, privacy, cyber and other aspects of digital transformation. The purpose of the scoping review is to chart evidence on RFID deployment in apparel, fashion, textile, and transferable product contexts, focusing on traceability, anti-counterfeiting, product visibility, and implementation conditions in apparel, fashion, and textile supply chains, as well as in sustainability contexts. The review process followed scoping review guidance and its protocol. Evidence was found in the following formats: EndNote XML/export records, Covidence screening (title/abstract), Covidence screening outputs (included study exports), and uploaded full-text PDFs. Documents were classified by source type, study design, context, technology focus, purpose, key findings, relevance to sustainability, limitations, and role in the synthesis. The results show that RFID evidence is strongest in product identification, item-level visibility, secure inventory search, manufacturing data capture, logistics tracking, asset traceability, and operational efficiency. Full article

Textile waste has become a major environmental challenge associated with increasing levels of production and consumption in the fashion industry. The fast fashion business model, characterised by rapid production cycles, low prices, and frequent replacement of clothing items, contributes significantly to growing volumes of textile waste and the depletion of natural resources. This study examines students’ perceptions of the environmental impacts of textile waste and fast fashion, with particular emphasis on sustainable consumption practices and textile waste management in Croatia. The study combines a review of the scientific literature with an online questionnaire survey conducted among a non-probability convenience sample of 79 students enrolled in different study programmes in Croatia. The results indicate a high level of environmental awareness and familiarity with textile waste issues among respondents. However, despite generally positive attitudes towards sustainability, willingness to modify purchasing behaviour or pay higher prices for sustainable clothing remained limited, indicating a clear attitude–behaviour gap. Price emerged as a particularly important factor influencing purchasing decisions, while limited access to textile collection facilities was identified as an important barrier to proper textile waste management. Chi-square tests of independence did not identify statistically significant associations between environmental concern and support for sustainable fashion or between level of education and the examined sustainability-related consumption responses. The findings suggest that environmental awareness alone may not be sufficient to encourage sustainable consumption and highlight the importance of combining environmental education with economically accessible sustainable alternatives and adequate textile collection infrastructure. The study provides exploratory insight into the relationship between environmental awareness, consumer behaviour, and self-reported textile management practices among the surveyed students and contributes to the discussion on promoting more sustainable textile consumption within a circular economy. Full article

This study compares three AI platforms, Google NotebookLM (Google Labs, May 2026 release/access), ChatGPT-4o, and Gemini 1.5 Pro, for systematic literature review (SLR) tasks in sustainable textile and fashion research. A corpus of 40 peer-reviewed articles (2019–2025) was queried using 12 standardized prompts across four dimensions: source traceability, thematic synthesis, research gap identification, and output utility. NotebookLM achieved the highest weighted score (8.63/10) due to its document-grounded, structurally constrained architecture, which produced no out-of-corpus citations under the conditions of this study. ChatGPT-4o (8.50/10) excelled in narrative synthesis; Gemini 1.5 Pro (7.78/10) produced superior structured tables. Five corpus-grounded and two inferred gaps, including XAI, Federated Learning, and Edge AI, were identified. A four-step hybrid AI workflow is proposed. Full article

The growing convergence of digital transformation and sustainability is reshaping value creation across industries, particularly in the fashion sector, where the transition towards circular business models has become increasingly important. Although research on circular economy, digital transformation, and servitization has expanded considerably, limited attention has been devoted to how digitally enabled service systems support circular value creation during the post-purchase stage of the product lifecycle. This study examines how digital servitization is operationalised within the fashion ecosystem through a qualitative, theory-informed multiple-case study based on systematic website content analysis of 14 Italian B Corp organisations. It proposes a dual-cycle analytical framework comprising a Product–Service–Product (P-S-P) material loop and a Service–Product–Service (S-P-S) information loop, representing complementary mechanisms of material recirculation and digitally enabled lifecycle information exchange. The findings indicate that digital servitization is more frequently operationalised through material-oriented service mechanisms than through digitally enabled lifecycle information infrastructures, suggesting uneven development of the two complementary architectures. Observable implementation also differs across value chain positions, with downstream organisations exhibiting more customer-facing lifecycle service configurations, whereas upstream actors primarily contribute through enabling capabilities that are only partially captured by the framework. The study contributes by introducing an analytical framework that distinguishes complementary material and informational mechanisms of digital servitization, providing an exploratory basis for analysing observable circular service configurations across the fashion value chain. Full article

Sustainable apparel supply chain research is dominated by the fashion sector, while the specific operational, technical, institutional, logistics, and security requirements of military apparel supply chains remain insufficiently integrated into existing conceptual frameworks. This study aims to develop a conceptual model for sustainable military apparel supply chain management. A narrative literature review was used to identify source determinants derived from fashion supply chain research, followed by a sectoral analysis of military apparel supply chains. The determinants were then adapted using an adaptation matrix based on four transformation rules: functional, actor-related, restrictive, and extending transformation. The analysis identified six adaptive conditions defining the admissibility of sustainable solutions and nine target determinants grouped into four management pillars. These elements were integrated into the House of Sustainable Military Apparel Supply Chain Management (HoSMASC), in which the adaptive conditions form a qualifying foundation and the target determinants form pillars subject to graded assessment. A preliminary assessment matrix was also developed, combining a binary, conjunctive evaluation of the foundation with a 0–2 assessment of the determinants within the pillars. The model provides a structured framework for preliminary diagnosis and design support but remains conceptual and requires empirical validation through expert assessment and case studies. Full article

The textile, apparel, and fashion (TAF) industry generates significant environmental burdens across its entire supply chain. As the global textile recycling market expands, a systematic framework for classifying exhibitors and assessing their sustainability-related characteristics is increasingly needed. This study analyzes exhibitors at the 2026 Textiles Recycling Expo USA, the first specialized textile recycling exhibition in North America, to develop an exploratory sustainability assessment framework. Using qualitative content analysis, 78 exhibiting companies were categorized into four functional groups: (1) Hard-tech Infrastructure, (2) Chemical & Material Innovation, (3) Logistics & Waste Management, and (4) Knowledge & Support Services. Based on a review of sustainability assessment literature in the TAF industry, a four-dimensional framework was developed, encompassing Material Renewability, Process Sustainability, End-of-Life Options, and Technical & Digital Attributes. For a preliminary pilot application, 11 companies were purposively selected and evaluated by eight experts using defined key performance indicators (KPIs). The total scores ranged from 10.3 to 16.3 out of 20, with ESO RECYCLING Società Benefit receiving the highest overall score (16.3), followed by MARGASA (15.8). Across the evaluated companies, Technical & Digital Attributes generally showed relatively lower scores than the other dimensions, indicating comparatively limited publicly evidenced digital traceability capabilities. These findings demonstrate the preliminary applicability of the proposed framework for characterizing heterogeneous exhibitors while highlighting the need for further refinement and validation using larger and more diverse samples. Full article

Environmental Impact Assessment (EIA) and Life Cycle Assessment (LCA) have become the dominant tools through which fashion judges whether a material is sustainable. These tools were built for materials that behave predictably: stable, standardised, manufactured to specification. But a growing class of biofabricated materials is not manufactured—it is grown. This paper argues, from the perspective of a designer–researcher who spent a year cultivating and designing with bacterial cellulose (BC), that applying these frameworks to living materials does not produce neutral measurements. It flattens a material whose environmental story is written through process, not fixed at origin. Drawing on a year of practice-led experimentation at Northumbria University, I present three moments where the material refused to behave as a single, assessable object: a glycerol conditioning concentration arrived at through iterative testing that diverged from standard protocol; cultivation variability that produced materially distinct outcomes from nominally identical processes; and a laser-cut sample that distorted in sunlight at a public exhibition, revealing how post-processing and use conditions—not composition alone—govern whether BC’s much-cited biodegradability actually holds. Read through a maker’s lens, these are not technical failures to be smoothed over—they are evidence. I argue that EIA for living materials must become contextual, process-aware, and willing to recognise the designer–practitioner, working at the material frontier, as a legitimate producer of environmental knowledge. Full article

The transition to sustainable energy is critical for addressing global climate change. Hydrogen production, particularly via electrolysis, has emerged as a key solution, offering the potential for low-carbon energy across various sectors. This paper conducts a spatiotemporal life cycle analysis of electrolytic hydrogen production in Australia under time-varying CO₂ management schemes. Three scenarios are studied. The baseline scenario studies hydrogen production at a fixed rate of 20 kg/h, resulting in monthly carbon emissions of 30–500 metric tons of CO₂, depending on the Australian state and chosen month. Variable production scenario 1 reduces hydrogen production in a tiered fashion as the grid’s carbon intensity increases, resulting in monthly carbon emissions of 30–110 metric tons of CO₂, depending on the Australian state and chosen month. Finally, variable production scenario 2 restricts hydrogen production to periods when the life cycle carbon intensity (LCA CO₂eq) of electricity falls below a predefined threshold of 0.6 kg CO₂ per kg H₂, thereby qualifying for hydrogen tax credits and resulting in monthly carbon emissions of 0.1–0.6 metric tons of CO₂ in Tasmania. Leveraging real-time data from the Electricity Mapping database and real-time electricity cost data from the AEMO database, the three scenarios study the effect of dynamically adjusting hydrogen output to reduce both emissions and production costs. Furthermore, the integration of hydrogen tax credits significantly enhances cost-effectiveness, offering a viable pathway for widespread adoption. This study concludes that dynamic, real-time operation, coupled with financial incentives, offers a promising approach to enhancing the sustainability and economic viability of hydrogen production. Full article

The transition to a circular economy requires professionals to adopt new strategies and a systemic approach to product development. This shift demands continuous learning and the development of new competencies to understand and apply circular economy principles. In this context, innovative educational approaches that foster engagement and lifelong learning (LLL) are essential. Gamification can support this process by enhancing motivation, creativity, problem-solving, and knowledge retention, while interactive tools help learners critically examine and operationalise circular economy principles. This article discusses the design and application of the “Circularity Deck of Cards,” a learning resource developed as part of a European-funded project Be@t, to facilitate the circular design of products and services. The study follows a mixed-methodological approach encompassing three phases: a systematic mapping of international tools and methodological approaches; the conceptual and visual development of the resource; and its implementation and evaluation through a workshop involving undergraduate, master’s, and doctoral students and researchers in fashion design and textile engineering in Portugal. The data were collected using a questionnaire that combined quantitative and qualitative questions, designed to assess the receptiveness to, challenges of, and opportunities arising from gamification in the teaching of circular design. The findings indicate that participants responded positively to the tool, recognising its value as both a pedagogical resource and a professional instrument for promoting sustainability and circularity in the textile and clothing industry. Ultimately, gamification catalyses training students, designers, and industry professionals to address the challenges of circularity, fostering new perspectives on circular design in professional practice. Full article

Generative artificial intelligence (GenAI) is reshaping fashion design by expanding creative possibilities and accelerating innovation. For independent designer brands, which rely on originality, distinctive aesthetics, and creative identity, GenAI offers opportunities to sustain innovation while raising concerns about authenticity and consumer trust. However, consumer responses toward AI-generated clothing (AGC) among AGC-interested young Chinese consumers remain underexplored. This study explores factors influencing their attitudes and purchase intention toward AGC. Drawing on a TPB–TCV-based integrated framework, this study develops an integrated model incorporating consumption value dimensions, perceived effort of the brand in design (PEBD), generative quality (GQ), and AI creativity (AIC). Based on 568 valid questionnaires, PLS-SEM was employed, with multi-group analysis as a supplementary analysis. The results show that attitude plays a key mediating role in explaining purchase intention. Specifically, PEBD and subjective norm significantly predict purchase intention, while PEBD also indirectly influences purchase intention through attitude. Emotional, epistemic, and social values, PEBD, GQ, and AIC significantly contribute to attitude formation, whereas only PEBD and subjective norm demonstrate significant direct effects on purchase intention. These findings provide managerial insights for independent designer brands seeking to apply GenAI while considering consumer perceptions of creativity, originality, and value in shaping AGC purchase intention. Full article

The increasing environmental impact of the textile industry has heightened interest in sustainable consumption practices, particularly second-hand clothing consumption. However, instruments assessing attitudes toward second-hand clothing remain limited. This study aimed to develop a scale to assess university students’ perceptions, sustainability orientations, values, and attitudes toward second-hand clothing consumption and to provide evidence of its psychometric properties. An initial pool of 45 items was generated through a literature review and focus group interviews with students from 14 universities representing different geographical regions of Türkiye. Exploratory Factor Analysis (EFA) was conducted using data from 244 university students. After removing nine items, a 36-item, eight-factor structure accounted for 66.43% of the total variance. The factors were labeled Saving, Fashion, Social Interaction, Spiritual Well-Being, Brand Orientation, Sustainability, Trust, and Nostalgia. Confirmatory Factor Analysis (CFA) performed on an independent sample supported the proposed structure and demonstrated an acceptable model fit (χ²/df = 2.16; CFI = 0.854; TLI = 0.838; RMSEA = 0.069; SRMR = 0.074). Cronbach’s alpha coefficients ranged from 0.712 to 0.913. Overall, the findings indicate that the proposed scale demonstrates acceptable psychometric properties and has the potential to assess university students’ attitudes toward second-hand clothing consumption in future research. Full article

The fashion industry faces growing pressure to demonstrate credible sustainability performance across environmental, social and economic dimensions, yet integrated approaches remain underdeveloped, particularly for small and medium-sized enterprises and social enterprises operating in circular textile systems. This article examines the case of INS3RTEGA, a Spanish textile social enterprise that combines post-consumer textile waste management with protected employment for people with disabilities. Using an exploratory single-case design informed by Triple Bottom Line thinking, the study develops a pragmatic assessment strategy that combines a partial Social Return on Investment (SROI)-style calculation, a simplified carbon-based estimation informed by life cycle thinking, and a set of non-monetised social inclusion and employment indicators. The results reveal a distinctive configuration of integrated sustainability performance: substantial avoided climate-related burden and high textile recovery rates, strong structural inclusion outcomes through disability-inclusive employment, and a modest partial monetised return under conservative and incomplete valuation assumptions. The case illustrates how socially inclusive circular fashion models may generate meaningful sustainability value that remains only partially visible through conventional financial or fully monetised metrics. The article discusses methodological implications for hybrid impact assessment in resource-constrained organisations and policy implications for the emerging European framework on sustainable and circular textiles. Full article

This study investigated the implications of integrating artificial intelligence (AI) technologies into fashion design education and their relationship with supporting sustainable design practices. A descriptive–analytical approach was adopted, and an online questionnaire was administered to a sample of 404 female students and graduates specializing in fashion design in Saudi Arabia. The study examined the perceived usefulness of AI technologies in supporting sustainable design, the level of sustainable design self-efficacy, the relationship between these two variables, and differences associated with selected demographic variables. In addition, two optional open-ended questions provided complementary qualitative insights into participants’ perceptions of AI in sustainable fashion design. The findings revealed a high level of perceived usefulness of AI technologies in supporting sustainable design practices, as well as a high level of sustainable design self-efficacy among the participants. Statistically significant differences were found in perceived usefulness according to participants’ level of experience with AI tools and frequency of use, in favor of those with greater experience and more frequent use. The results also showed a strong positive relationship between perceived usefulness and sustainable design self-efficacy, along with statistically significant differences according to academic status, educational level, and geographic region. The qualitative findings further highlighted the role of AI in enhancing creativity, improving design efficiency, and reducing waste, while also pointing to challenges related to AI literacy, intellectual property, and ethical use. The study contributes empirical evidence from fashion design education in Saudi Arabia, a context that remains underrepresented in previous research, and emphasizes the importance of integrating AI technologies into fashion design education through educational and ethical frameworks that promote responsible AI use and sustainability-oriented design competencies. Full article