Search Results (154)

Urban congestion is simultaneously influenced by heterogeneous spatio-temporal travel demands, the topology and spatial characteristics of road networks, and the interplay between multiple travel modes. As a critical component of solutions towards a greener and more sustainable transportation, bike-sharing systems have great potential in reducing carbon emissions, improving public health, and alleviating congestion by substituting short-distance motorized trips. Benefiting from flexible accessibility and usage, dockless bike-sharing has gained wide popularity and revived the fashion of cycling in cities. In this study, we reveal that the widely adopted detour ratio alone cannot effectively reflect congestion levels at the route level. Using large-scale dockless bike-sharing data and taxi trajectory data in Beijing, we quantitatively examine the relationships between cycling flow, motor vehicle traffic and road network structure. In addition, the proposed cycling-traffic-weighted detour ratio can prescreen potentially inefficient cycling routes, which can assist targeted infrastructure optimization and evidence-based urban planning. Full article

Composed Image Retrieval (CIR) aims to search a target database for images that best align with a user’s intent, conditioned on a reference image paired with modification requirements. Existing CIR architectures typically treat the visual reference and the textual modification as symmetrical inputs, fusing their features into a shared latent embedding space. From a user-centric perspective, however, these multi-modal inputs serve fundamentally asymmetric roles: the reference image acts as a soft semantic anchor, whereas the modification text functions as an explicit requirement specifying precise visual changes. Because current models optimize composition predominantly at a global representation level, these non-negotiable logical constraints are frequently violated during inference, leading to retrieval results that fail to satisfy the user’s explicit instructions. To mitigate this limitation, we introduce a novel, training-free verification framework for fashion retrieval that enforces textual constraint adherence without sacrificing the expressive flexibility of open-vocabulary natural language. Our approach leverages schema-conditioned large language models to extract explicit, structured logical constraints from raw queries during post-processing. A downstream vision-language agent subsequently verifies these constraints against the top retrieved candidate pool to penalize non-compliant images and optimize candidate ordering. Extensive evaluations across standard fashion benchmarks demonstrate that our plug-in framework consistently and significantly enhances the recall metrics of state-of-the-art supervised and zero-shot CIR baselines. Full article

The fashion industry’s business is becoming increasingly complicated and active. This industry is expected to be highly competitive, particularly in the retail sector. Therefore, this research aims to examine the impact of supply chain information sharing and quality management on firm performance, with supply chain agility as a mediating variable, in the Asian fashion industry. A total of 169 participants from the fashion sector in a developing country were surveyed. The proposed hypotheses were examined using a quantitative approach, employing Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS to assess and validate the measurement model. The results indicate that supply chain information sharing and quality management have a significant impact on a firm’s performance. Similarly, the sharing of supply chain information and quality management has a significant impact on firm performance by mediating supply chain agility. The study offers actionable insights for managers in volatile fashion supply chains. Firms can enhance performance by sharing real-time demand and inventory information, strengthening key quality practices, and adopting flexible, data-driven production processes. Integrating information sharing, quality management, and agility enables faster responses to shifting consumer trends, thereby improving overall competitiveness in fast-fashion environments. This study offers valuable guidance for supply chain professionals seeking to enhance practices within their networks. The results underscore the strategic importance of information sharing and quality management in promoting agility, an essential capability for achieving a competitive advantage. Additionally, the insights generated are relevant to practitioners, policymakers, and industry leaders aiming to strengthen supply chain responsiveness and resilience. Full article

How might beginning professionals learn a sense of belonging founded upon the norms of the profession and acquire a professional gaze along with their professional voice? We argue for a conceptual model founded upon the interplay between navigating liminality, the art of “storying” and sharing professional experiences, and, lastly, recognising the importance of an enabling context captured by the Japanese concept of ba (from the Japanese word 場, meaning a shared meeting place for emerging relationships). The education of correctional and police officers offers illustrative examples of professional conversations that occur in an iterative fashion, often in confined places such as on night watch in an office or car setting. We contend that the art of “storying” professional experiences and story-sharing are key practices used to come to terms with and navigate critical events and accompanying sensations and experiences. We draw upon the seminal works of Rousseau and more contemporary educational theorists and conclude by proposing a programme of future research. The defining character of this contribution is to emphasise the importance of professional stories and storying that engage with rather than discount emotions. This underpins our desire to acknowledge the work of Rousseau known for “feeling before thinking,” and the work of Brecht, who asserted the priority of cognitive thought in emotionally charged aesthetic experiences. Full article

The transition to circular models in fashion and textiles requires changes that go beyond technical innovation. The literature recognises that systemic change depends on the transformation of shared meanings around consumption and production, and that spaces for co-design and collaborative learning are crucial to generating this transformation. This article documents how Living Labs operate in this capacity, analysing the Madeback Circular Fashion Festival (May–November 2025), a pilot project of the Fashion & Textile Living Lab at the Politecnico di Milano. The study employs the Living Lab Integrative Process (LLIP) as both a design framework and an analytical lens. Adopting a qualitative and participatory method, the study documents how the three spaces of the LLIP—Problem Space, Solution Space and Implementation Space—simultaneously structured both design innovation and empirical analysis. The results point to three main contributions: (i) Living Labs can function as cultural infrastructures in which performative and narrative dimensions may contribute to the gradual normalisation of alternative practices; (ii) the Quadruple Helix operates as a living process characterised by distributed intentionality and emerging trust; and (iii) transformative learning appears through the co-production of knowledge in embodied and relational practices. The article identifies contextual factors that enabled the project—from its location in a design university to its multi-year funding—and the related constraints on transferability, concluding that Living Labs are promising infrastructures for sustainable transitions when they consciously integrate performative, cultural and relational dimensions. Full article

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

Objective: This study aimed to investigate aspects of sexual response in cisgender women by querying what participants deem to be important physiological and subjective components of sexual arousal. It was also explored whether education about the role of genital blood flow influenced participant responses. Methods: Standard sexuality-based questionnaires were administered assessing function, desire, flexibility, satisfaction, and history, prior to administering a short semi-structured interview. Experiences of sexual arousal were explored in the interview in an open-ended fashion. A brief educational video condition was shared with half of the participants at random. We explored whether being presented additional information about genital function changed the way women describe their physiological response. Those in the control group completed the interview questions once. Those in the educational condition group completed the interview, watched the brief educational video and then repeated the interview questions. Following the interview, all participants completed a brief follow-up questionnaire assessing preferred arousal terminology. Results: The sample size included 30 cisgender women with a mean age of 21.10 (4.38), with 70% in a committed relationship. Additionally, there were no group difference found with those who reported a history of sexual trauma/abuse vs. no trauma/abuse in regard to sexual function, satisfaction, distress and flexibility. The physical arousal sensations described most often in the interview included lubrication (n = 27), blood flow (n = 23), and pulsating (n = 9), whereas, in the ranked term analysis, the three most highly ranked genital sensations were wetness, throbbing and tingling. For non-genital sensations, those most often reported in the interviews included nipples/breast changes (n = 17), skin sensitivity (n = 13), and changes in body temperature (n = 12), whereas them most highly ranked non-genital sensations were heart rate increase, hardness of nipples/breast changes, and skin sensitivity. There were no group differences in the reporting of full-body or genital sensations and the frequency of use of terminology related to blood flow. The two most important themes emerging from the qualitative analysis included the distinct themes of subjective and physiological arousal. The majority of participants placed an emphasis on subjective arousal, deeming it the most important part of their sexual response, with physiological arousal largely deemed important only when subjective arousal was also present. Conclusions: The same themes were present in both groups, indicating that the brief educational video was unlikely to have influenced the way women described their physiological arousal. Participants in both groups placed a dominant emphasis on sensations related to genital blood flow and the importance of subjective arousal. Full article

We study motif-based optimization for sparse multilayer perceptrons (MLPs), where weights are shared and updated at the level of small neuron groups (‘motifs’) rather than individual connections. Building on Sparse Evolutionary Training (SET), our approach reduces the number of unique parameters and redundant multiply–accumulate operations by exploiting block-structured sparsity. Across Fashion-MNIST and a lung X-ray dataset, our Motif-SET improves training/inference efficiency with modest accuracy trade-offs, and we provide a principled recipe to choose motif size based on accuracy and efficiency budgets. We further compare against representative modern sparse training and compression methods, analyze failure modes such as overly large motifs, and outline real-world constraints on mobile/embedded targets. Our results and ablations indicate that motif size $m=2$ often offers a strong balance between compute and accuracy under resource constraints. Full article

This article examines the role of digital communication, social media, and peer influence in Generation Z’s transition from fast fashion to more sustainable consumption practices. Building on sustainability and social influence theories, this study applies a mixed-methods design that combines qualitative content analysis of social media discourse with a quantitative online survey (n = 202). The survey instrument, validated by a panel of experts, measured four dimensions—digital communication, peer influence, sustainable attitudes, and sustainable behaviors—using Likert-type scales with adequate reliability (Cronbach’s α ≥ 0.70). The statistical analyses included descriptive statistics, Pearson correlations, and mean comparison tests (t-test, ANOVA). The results show that digital platforms not only raise awareness but also normalize sustainable choices through peer validation and community engagement. Strong correlations confirm that peer influence mediates the relationship between exposure to sustainability content and the adoption of responsible behaviors, while perceptions of brand sustainability show weaker associations with purchase intention. This study highlights a persistent attitude–behavior gap and identifies opportunities for more effective digital engagement. The findings contribute to the literature on sustainable fashion consumption by clarifying the communicative mechanisms shaping Gen Z’s decisions. Practical implications are offered for brands, policymakers, and educators seeking to foster authentic and inclusive sustainability strategies, particularly in addressing gender differences in sustainable adoption. Full article

The fashion industry is facing increasing pressure to adopt sustainable practices given its significant impact on the environment. This research aims to analyze the implications of marketing strategies in the fashion industry’s transition towards a sustainable and responsible business model. The study starts from the premise that marketing can influence consumer behavior and turn sustainability into a competitive advantage. To investigate this aspect, SmartPLS software was used and hypotheses were tested on the relationship between marketing strategies to educate and sensitize consumers on sustainability issues in the fashion industry and the creation of a sustainably engaged community. Moreover, it becomes essential to collaborate with non-governmental organizations and other brands that share their sustainability values. The research was based on a sample of 227 respondents, and the data were analyzed using structural equation modeling. The results indicate that marketing strategies that promote transparency in supply chain and production processes, enhance brand reputation and credibility and, promote innovation in sustainable materials and production processes through marketing strategies contributing to creating an engaged community, as well as through brand commitment to sustainability through concrete actions and access to new markets and growth opportunities. Marketing strategies to educate and sensitize consumers on sustainability issues in the fashion industry contribute to increasing consumer interest in sustainable products. The implications of the study highlight the need for coherent marketing approaches to support the sustainable transformation of the fashion industry. Full article

This research examines the governance of carbon rights in comparison with 7 other countries, focusing on Vietnam’s carbon markets and Reducing Emissions from Deforestation and Forest Degradation in Developing Countries implementation. Through constitutional theory and comparative analysis, the study explores carbon rights and their governance frameworks. It utilizes surveys, in-depth interviews, and literature reviews to scrutinize governance mechanisms. A comparative analysis of Vietnam with countries such as Australia, New Zealand, Sweden, Brazil, Democratic Republic of Congo, Indonesia, and the Philippines was performed. It highlights differences in legal, institutional, and policy frameworks. Australia and New Zealand, early adopters of carbon rights policies promoting private ownership, have developed strong markets. In contrast, Indonesia and other Global South nations are still evolving their frameworks, with a focus on state-controlled systems that restrict participation and equity. The findings indicate substantial gaps in Vietnam’s carbon rights governance compared to other countries, especially in terms of legal clarity, stakeholder engagement, and policy coherence. Accordingly, this study recommends that Vietnam should adopt a robust legal framework for carbon rights, improve transparency in carbon markets, and integrate Reducing Emissions from Deforestation and Forest Degradation in Developing Countries strategies within broader environmental governance objectives. Vietnam’s carbon rights ought to be designated as national assets to ensure equitable distribution among various forest ownership groups. Benefit-sharing mechanisms could be fashioned following the successful implementation of the Payment for Forest Environmental Services policy. The research concludes that, with these enhancements, Vietnam could emerge as a key player in the global carbon market and effectively leverage Reducing Emissions from Deforestation and Forest Degradation in Developing Countries for sustainable development and climate objectives. Full article

In this paper, we address the challenge of dynamic evolution of user preferences and propose an attribute-sequence-based recommendation model to improve the accuracy and interpretability of recommendation systems. Traditional approaches usually rely on item sequences to model user behavior, but ignore the potential value of attributes shared among different items for preference characterization. To this end, this paper innovatively replaces items in user interaction sequences with attributes, constructs attribute sequences to capture fine-grained preference changes, and reinforces the prioritization of current interests by maintaining the latest state of attributes. Meanwhile, the item–attribute relationship is modeled using LightGCN and a variant of GAT, fusing multi-level features using gated attention mechanism, and introducing rotary encoding to enhance the flexibility of sequence modeling. Experiments on four real datasets (Beauty, Video Games, Men, and Fashion) showed that the model in this paper significantly outperformed the benchmark model in both NDCG@10 and Hit Ratio@10 metrics, with a highest improvement of 6.435% and 3.613%, respectively. The ablation experiments further validated the key role of attribute aggregation and sequence modeling in capturing user preference dynamics. This work provides a new concept for recommender systems that balances fine-grained preference evolution with efficient sequence modeling. Full article

Federated learning represents a newly emerging methodology in the field of machine learning that enables distributed agents to collaboratively learn a centralized model without sharing their raw data. Some scholars have already proposed many first-order algorithms and second-order algorithms for federated learning to reduce communication costs and speed up convergence. However, these algorithms generally rely on gradient or Hessian information, and we find it difficult to solve such federated optimization problems when the analytical expression of the loss function is not available, that is, when gradient information is not available. Therefore, we employed derivative-free federated zero-order optimization in this paper, which does not rely on specific gradient information, but instead utilizes the changes in function values or model outputs to estimate the optimization direction. Furthermore, to enhance the performance of derivative-free zero-order optimization, we propose an effective adaptive algorithm that can dynamically adjust the learning rate and other hyperparameters based on the performance during the optimization process, aiming to accelerate convergence. We rigorously analyze the convergence of our approach, and the experimental findings demonstrate our method can indeed achieve faster convergence speed on the MNIST, CIFAR-10 and Fashion-MNIST datasets in cases where gradient information is not available. Full article

Industry 4.0 (I4.0) and Industry 5.0 (I5.0) represent important changes in industrial paradigms. I4.0 is centered on efficiency and competitiveness, and I5.0 adds sustainability, human-centricity, and resilience to the framework. Despite their growing relevance, much of the existing research remains techno-centric, neglecting the sociocultural and institutional forces shaping them. This study investigates how the transition from I4.0 to I5.0 is occurring using an institutional perspective. A qualitative methodology was employed, combining theoretical synthesis and secondary data analysis to develop an integrative model. The proposed model draws on insights from Institutional Theory, Scandinavian Institutionalism, Management Fashion, and Quintuple Helix, emphasizing the role of translation and diffusion in institutionalizing these paradigms. We maintain that both of them are fundamentally discursive, shaped by institutional pressures, shared meanings, and stakeholder interactions. I4.0 already allows for a heterogeneous vision adjusted to different perspectives and stakeholders. I5.0 goes further by responding to criticism about social and environmental issues and introducing resilience, especially after the COVID-19 pandemic and the ongoing climate crisis. As a result, I5.0 aligns with a broader range of actors and interests, increasing its potential for widespread acceptance and long-term impact. This research challenges deterministic views of technology, arguing that this new industrial revolution is not eminently technology-driven but instead emphasizes the central role of discourse and institutional processes in shaping its development. 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