Search Results (3)

With the increasing prominence of sustainable consumption and the rising influence of Generation Z in the fashion market, secondhand fashion e-commerce platforms have become essential carriers of green fashion. Although AI-assisted recommendation mechanisms are widely embedded in these platforms, their psychological and behavioral effects on users’ continuous use and social engagement remain insufficiently examined. To address this gap, this study incorporates the Stimulus–Organism–Response (SOR) framework to investigate the psychological reaction pathways and behavioral intentions of Generation Z users within Human-AI Collaboration-enabled green e-commerce environments. Three AI-driven service stimuli—Human-AI Collaborative Recommendation Perception, AI Interaction Transparency, and Perceived Personalization—were conceptualized as stimulus variables; Psychological Immersion, Emotional Triggering, Cognitive Engagement, and Platform Trust were modeled as organism variables; and Continuous Use Intention and Social Sharing Intention served as behavioral response variables. Based on 498 valid samples analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), the results demonstrate strong empirical support for all proposed hypotheses. Specifically, AI-driven stimuli significantly and positively influence psychological responses, which subsequently strengthen users’ continuous usage and social sharing intentions. This research provides theoretical insights for developing Human-AI Collaboration-enabled service systems that balance efficiency and emotional resonance on green e-commerce platforms, and offers practical implications for promoting sustainable fashion values among younger consumers. 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

Online secondhand resale platforms are a booming industry involving the growing recognition of various economic, environmental, and recreational benefits in buying and selling used items. This preliminary study explores technology-based strategies for online secondhand platforms, which contributed to the resale industry’s steady growth and digital transformation. Through a variety of literature, this study established a basis for developing research on technological innovations in online resale platforms. A mixed method was used to collect both quantitative and qualitative data to investigate and understand the features of resale e-commerce. Case studies of four online secondhand resale platforms specializing in general goods and fashion helped identify a variety of technological strategies that were later analyzed based on the technology acceptance model (TAM). Survey data from respondents in their twenties and thirties living in South Korea indicated features that promote safe transactions, engaging user experience and user interface design, and individual compatibility as most effective in influencing users’ resale platform usage. Features that involve high technology, such as virtual reality and machine learning, had the least impact on users’ usage. Data gathered from follow-up interviews showing the recurring theme of unfamiliarity with the technological features corroborated the survey findings. Analyzing qualitative data from expert interviews generated key concepts in future trends in online resale platform strategies, including effective data management. Based on this study’s findings, the digitalization and onlineization of the online secondhand resale industry are likely to continue with the implementation of various strategies that contribute to users’ perceptions of usefulness, ease-of-use, and enjoyment, increasing users’ satisfaction and, hence, the actual usage of these platforms. The proliferation of secondary e-commerce will facilitate a shared culture that values sustainable consumption in online platforms and promote sustainability in the retail industry. Full article