Search Results (39)

This study examines the socio-economic and behavioral factors influencing sustainable consumption through secondhand clothing purchases among young consumers in Hanoi, Vietnam. By addressing the changing consumption patterns, this research contributes to understanding how youth behavior supports the transition toward sustainability in emerging urban markets. This research integrates the Theory of Planned Behavior (TPB) with additional constructs such as perceived economic benefits, environmental concern, perceived risk, shopping experience, and gender differences to provide an integrated socio-economic framework. Data were collected through a structured questionnaire administered to university students and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results indicate that perceived economic benefits and subjective norms are the strongest predictors of purchase intention across both general and luxury secondhand fashion segments, emphasizing affordability and social acceptance. Environmental concern and attitude also positively influence general secondhand purchase intentions, while perceived behavioral control notably impacts luxury secondhand purchases. Contrary to prior studies, perceived risk was found to be insignificant, and male consumers exhibited a higher engagement rate than females in this context. These findings underscore the complex interplay of economic, social, and environmental dimensions shaping sustainable fashion consumption among youth. This study suggests targeted marketing and policy strategies to promote sustainable consumption and supports the expansion of circular economy practices in emerging urban markets. Limitations related to sample scope and self-reported data warrant further research to generalize the findings and explore additional moderating variables. Full article

This study investigates sustainable consumption patterns across different generations (Centennials, Millennials, Generation X, and Baby Boomers) and genders in Colombia, an emerging country. Using a quantitative approach, a 38-item questionnaire was administered to 736 participants. Multinomial regression analysis revealed statistically significant differences in sustainable consumption patterns based on generation and gender. Generation Z prefers buying and extending the use of second-hand clothing, while Generation Y focuses on reducing excessive consumption. Generations X and Baby Boomers are motivated by preserving resources for future generations and researching sustainable products before purchasing. Women show a greater inclination toward sustainable consumption than men. These findings contribute to understanding generational and gender differences in sustainable consumption behaviors within an emerging market context. Full article

Demand for clothing is estimated to increase globally by 4.5% per year, and secondhand clothing is often used to fill that demand. A clear understanding of the environmental impact of secondhand items would support transparency around sustainability, which is a rising consumer concern. This study focuses on the characteristics of the fiber fragment material released during the laundering of secondhand, 100% cotton denim clothing, and the implications of secondhand clothing’s contribution of fiber fragments to the environment. The test method used was AATCC TM212-2021, with detergent, conditioned specimens, and filters. The specimens included thirteen pairs of secondhand men’s 100% cotton jeans (SHS) and two pairs of new jeans (CN controls). This study concluded that the amount of fiber fragmentation material shed by SHS was 23.2% of that shed by CN. While this is less than is shed by new clothing, there is still shed material to consider, including dyes and processing chemicals that can contribute to anthropogenic contamination of the environment. The fiber fragment size and frequency were found to have statistically significant differences between SHS (length 370.5 µm, diameter 16.9 µm, 3093 fiber fragments per filter) and CN (320.7 µm, 13.8 µm, and 5962 fiber fragments per filter). Full article

As global attention on environmental sustainability grows, the fashion industry is shifting towards circular models, with the second-hand clothing market emerging as a key pathway to sustainable development. In China, this market is rapidly evolving, with millennials and Generation Z showing strong interest in environmentally friendly and personalized fashion. This study investigates Chinese consumers’ motivations and barriers to purchasing second-hand clothing and examines the diversity of China’s sustainable fashion ecosystem. Using a mixed-methods approach of semi-structured interviews and surveys, the findings reveal that environmental awareness, economic affordability, and social influence drive purchase intentions, while hygiene concerns, societal perceptions, and trust in platforms act as barriers. The study also compares the roles of online platforms, offline vintage stores, and upcycling fashion brands, highlighting their complementarity across economic, cultural, and social dimensions. Online platforms offer efficiency and convenience, vintage stores build brand loyalty through cultural narratives, and upcycling brands merge creativity with sustainability. It also reflects on the cultural context shaping second-hand fashion adoption in China. The study suggests enhancing trust in platforms, promoting education, and leveraging social media campaigns to support future market development. Full article

Over 24 billion items of used clothing are traded annually from high- to low-income countries in a sector worth more than 4.9 billion dollars. Imported second-hand clothes are the primary source of garments for many of the world’s poorest people. The sustainability of this system and its contribution to the circular economy is explored. Results map the structure of used clothing networks. UN Comtrade data is analyzed to trace the major exporters and importers, and trade and NGO reports are explored to consider the environmental and economic impacts. Second-hand clothing imports have a negative effect on local clothing industries and cause environmental harm in developing countries. The article further explores how the second-hand clothing trade intersects with the circular economy and emerging patterns of clothing re-sale, such as the Vinted peer-to-peer retail platform. Rather than contributing to economic or environmental sustainability or a true circular economy, the second-hand clothing sector is facilitating the expanding consumption of fast fashion in developed economies, stifling industrial development and causing environmental damage via a form of ‘waste colonialism’ particularly in sub-Saharan Africa. Anti-poverty organizations like Oxfam play a contradictory role as they benefit from the trade, which is part of a wider fashion system that is unsustainable. Full article

Digital platforms in fashion e-commerce are progressively shaping sustainable consumption practices. This research explores the interplay between consumer behaviors toward recycled and second-hand fashion, and the adoption of digital platform-driven innovations. The analysis is based on a structured questionnaire and an online survey of 1000 consumers conducted in 2025, employing a combination of descriptive and inferential statistical techniques, including both cluster and factor analysis. The findings suggests that demographic factors—particularly age, education, and gender—significantly shape consumer attitudes toward digital innovations in fashion e-commerce apps. The analysis also confirms that the perceived effectiveness of AI and AR tools is significantly correlated with an increased interest in circular fashion options, including second-hand marketplaces and recycled clothing. The study emphasizes the strategic importance of platform features in fostering conscious fashion choices, thereby offering practical insights for retailers aiming to harmonize technological innovation with sustainability goals. Full article

This study integrates the Theory of Planned Behavior and the Theory of Consumption Values through a mixed-methods approach (structured interview and structural equation model) to investigate cross-platform disposal behaviors for idle clothing on social media and second-hand platform ecosystems. The study reconstructs traditional theoretical variables: psychological motivation dimension (platform-enabled green attitude, social circle environmental demonstration, and cross-platform behavioral control) and perceived value dimension (functional integration value perception, socialized emotional empowerment, and community identity value). Key findings: Cross-platform behavioral control is the strongest predictor of behavioral intention. In the value dimension, emotional value has the strongest direct impact on disposal intentions, functional integration is key to enhancing behavioral control, and community identity value most significantly impacts the platform-enabled green attitude and the social circle environmental demonstration. Finally, proposing a governance framework of “technological empowerment–emotional resonance–identity motivation”, offering theoretical foundations for optimizing platform interoperability and formulating digital environmental policies. Full article

The global school uniform industry, primarily driven by linear production models, significantly contributes to textile waste and environmental degradation. In Australia, over 2000 tons of school uniforms are discarded annually, highlighting the urgent need for sustainable alternatives. This study explores the integration of Circular Economy (CE) principles into school uniform systems through a case study of a private school in Victoria. Using a thematic approach, the research involved a parent survey with 106 participants and a focus group with 6 parents. The study identified financial, logistical, and socio-cultural factors influencing uniform consumption and disposal behaviors. Affordability emerged as the primary motivator for adopting second-hand uniforms (86%). However, barriers such as limited sizing, hygiene concerns, quality, and social stigma hinder wider adoption. Parents also expressed dissatisfaction with the current uniform design, material breathability, and durability, particularly in warmer climates. Despite increased awareness of sustainability (61% cited environmental concerns), actionable engagement remains low due to a lack of transparency and infrastructure. The study proposes a replicable circular uniform framework based on stakeholder co-design, reverse logistics, and curriculum-based sustainability education. These findings offer practical implications for policymakers, educators, and manufacturers aiming to reduce textile waste and promote CE adoption within the education sector. Full article

Background: Previous studies have demonstrated that involuntary smoking (e.g., secondhand smoke [SHS] and thirdhand smoke [THS]) is not only associated with an increased risk of several physical health problems, such as cardiovascular disease and cancer, but also impacts mental health, including depression and anxiety. However, the relationships between SHS and THS exposure and non-suicidal self-injury (NSSI), suicidal ideation (SI), and suicide attempts (SAs) remain unclear. Methods: Participants were recruited at a Chinese vocational college via voluntary online surveys conducted on campus. Self-reported SHS exposure was determined by the frequency of contact with smokers or detecting tobacco odors in living environments, while THS was assessed through regular contact with smoker-contaminated surfaces (e.g., clothing, furniture, textiles). Logistic regression analysis was performed to evaluate the associations of SHS and THS exposure with the prevalence of NSSI, SI, and SAs in never-smoking participants. Results: The study included 5716 participants (mean age = 19.3 years; females, 85.4%). The prevalence of SHS and THS exposure was 87.6% and 77.4%, with 8.8% reporting ≥15 min of SHS exposure on at least one day per week. After controlling for potential covariates, exposure to SHS (≥15 min on at least one day per week) was significantly associated with the odds of SAs (OR [95%CI] = 1.85 [1.17–2.91]). Additionally, daily THS exposure was significantly associated with increased past-year NSSI prevalence (2.35 [1.29–4.28]) compared to those without THS exposure, with similar associations observed for SI (2.11 [1.28–3.48]) and SAs (2.40 [1.23–4.69]). Conclusions: Exposure to SHS and THS was significantly associated with increased likelihood of NSSI, SI, and SAs among young adults at a Chinese vocational college. Further studies are needed to validate these associations across more diverse populations. Full article

Artificial intelligence (AI) is revolutionizing the fashion, textile, and clothing industries by enabling automated assessment of garment quality, condition, and recyclability, addressing key challenges in sustainability. This systematic review explores the applications of AI in evaluating clothing quality and condition within the framework of a circular economy, with a focus on supporting second-hand clothing resale, charitable donations by NGOs, and sustainable recycling practices. A total of 135 research resources were identified through searching academic databases including Google Scholar, Springer, ScienceDirect, IEEE, Taylor and Francis, and Sage journals. These publications were subsequently refined down to 49 based on selected inclusion criteria. The selection of these sources from diverse databases was undertaken to mitigate any potential bias in the selection process. By analyzing the effectiveness and challenges of related peer-reviewed articles, conference papers, and technical reports, this study highlights state-of-the-art methodologies such as convolutional neural networks (CNNs), hybrid models, and other machine vision systems. A critical aspect of this review is the examination and analysis of datasets used for model development, categorized and detailed in a comprehensive table to guide future research. Whilst the findings emphasize the potential of AI to enhance quality assurance in second-hand clothing markets, streamline textile sorting for donations and recycling, and reduce waste in the fashion industry, they also highlight gaps in the available datasets, often due to limited size and scope. The types of textiles captured were most commonly swatches of fabric, with 20 studies examining these, whereas whole garments were less frequently studied, with only 7 instances. This review concludes with insights into future research directions and the promising use of AI within fashion and textiles to facilitate a transition to a circular economy. This project was supported through RMIT University’s School of Fashion and Textiles internal seed funding (2024). Full article

This study investigates the shopping behavior of Generation Z towards second-hand clothing in Slovakia, focusing on in-store experiences and their relationship with emotions, gender, and environmental awareness. Data were collected from 340 respondents through an online survey conducted between November 2024 and January 2025. The results indicate that feelings such as authenticity, fun, and interest in finding fashionable items are significantly associated with gender. Across all five dimensions, women perceive second-hand clothing shopping more positively than men. The biggest difference between the sexes is that women find this shopping more fun, enjoyable, and authentic. Men tend to be slightly more skeptical in their evaluation, with the lowest average score (2.65) on the question of whether shopping is “fun”. The study also reveals a strong correlation between the shopping experience and consumer attitudes. Individuals with prior experience in buying second-hand clothing exhibit greater environmental awareness, a stronger emotional connection with clothing, and a higher likelihood of participating in clothing swap events. Conversely, those without experience often harbor prejudices related to hygiene and perceive second-hand shopping as time-consuming and inconvenient. These findings highlight the importance of in-store experiences and the role of emotions in shaping consumer behavior towards second-hand clothing. The results have implications for retailers and policymakers seeking to promote sustainable consumption practices and enhance the appeal of the second-hand clothing market. Full article

Secondhand clothing has undergone a significant transformation from a vital household asset in the pre-industrial era to a dynamic segment of global trade in the 21st century. However, the advent of fast fashion has led to overproduction and mass consumption of inexpensive garments, fueling a surge in the secondhand clothing trade. Between 2002 and 2022, the market value of this industry quadrupled, with exports accounting for 1.17% of total global clothing exports in 2022. This study examines global secondhand clothing exports using export competitiveness tools such as revealed comparative advantage (RCA), the index of export market penetration (IEMP), the trade intensity index (TII), unit values, market shares, and the compound annual growth rate (CAGR). The top eleven secondhand clothing exporting countries are analyzed for a ten year period (2013 to 2022) using the United Nations Commodity Trade Statistics Database. The analysis reveals notable trends: the United States and China dominate the market, while Pakistan and the UAE exhibit the highest growth rates. The study also reaffirmed that trade patterns for secondhand clothing continue to flow from the Global North—including China—to the Global South, a trend observed since the early 2000s. This research provides a comprehensive, current analysis of the ever growing secondhand clothing export market within the sustainable management of the secondhand clothing context. Full article

Driven by the increasing awareness of environmental protection and the demand for personalized fashion, China’s second-hand clothing market is developing rapidly. Chinese consumers have begun to accept second-hand clothing, and online platforms such as Xianyu and Zhier have promoted the widespread trading of second-hand clothing. This study explored the key factors influencing customer satisfaction in China’s sustainable second-hand clothing market. Using a mixed research approach, factors such as pricing strategy, product quality, brand image, customer service, market environment and promotions were identified. The conclusion of grounded theory is that price, product quality, brand reputation, customer service quality, economic environment and platform promotions have a strong impact on customer satisfaction. The Kano model highlights the sensitivity of customer service quality, economic environment and promotions in improving satisfaction. Price is crucial, confirming the price sensitivity of customers. Brand reputation and product quality significantly increase satisfaction. Customer satisfaction significantly affects the amount of sustainable recycling. This study improves the theoretical framework and research hypotheses, provides valuable insights for future research and practical applications and contributes to the sustainable development of the second-hand clothing market. Full article

Characterized by inexpensive and readily available products, fast fashion has increased the consumption and disposal of clothing, for which criticism has been significant due to its negative environmental and social impact. Therefore, transitioning to sustainable business models (SBMs) that balance profit with corporate social responsibility (CSR) is critical. This study explores sustainable value propositions in Polish Zero Waste fashion businesses, addressing the gap in research on SBMs. It also employs the theory of organizational paradoxes to examine tensions between profit maximization and CSR. Data were collected from 249 Polish Zero Waste companies listed on mapazerowaste.pl and analyzed through content analysis and statistical methods. Additionally, 21 YouTube videos from 2020 to 2022 were examined to study sustainable fashion promotion. Multiple coding and categorization schemes were used to identify themes, followed by frequency analysis and correspondence analysis. Second-hand clothing emerged as the most common value proposition (120 companies), reflecting consumer trends in resale. The repair sector with cobbler and leather repair services (55 companies) also showed a strong presence, highlighting demand for tailoring and upcycling services Rental services (2 companies) remain niche due to limited consumer acceptance. Promotion efforts on YouTube focus on building awareness of fast fashion’s impacts and teaching sustainable behaviors. Sustainable value propositions, exemplified by Polish Zero Waste businesses, synthesize profit and CSR strategies, addressing organizational paradoxes. These findings inform strategies to balance financial and socio-environmental goals, with implications for policy and practice in advancing sustainable fashion. Full article

The objective of this work is to develop a method for tracking human skeletal movements by integrating data from two synchronized video streams. To achieve this, two datasets were created, each consisting of four different rehabilitation exercise videos featuring various individuals in diverse environments and wearing different clothing. The prediction model is employed to create a dual-image stream system that enables the tracking of joint positions even when a joint is obscured in one of the streams. This system also mitigates depth coordinate errors by using data from both video streams. The final implementation successfully corrects the positions of the right elbow and wrist joints, though some depth error persists in the left hand. The results demonstrate that adding a second video camera, rotated 90° and aimed at the subject, can compensate for depth prediction inaccuracies, reducing errors by up to 0.4 m. By using a dual-camera setup and fusing the predicted human skeletal models, it is possible to construct a complete human model even when one camera does not capture all body parts and to refine depth coordinates through error correction using a linear regression model. Full article