Search Results (203)

The strategic decision to choose in-house production and outsourcing (make and buy) is one of the enormous research questions of international business studies. However, the dynamics of offshore mixed sourcing involving suppliers with varying capabilities remain under-explored. This study intends to elucidate how a firm optimizes the division of labour between an affiliated offshore factory and heterogeneous contract manufacture. We adopt a single-case study design to analyse a Japanese apparel firm operating in China. The empirical analysis using the plant-level data of both in-house and outsourcing Chinese factories reveals a clear strategic distinction: the affiliated factory specializes in High-Mix Low Volume (HMLV) production to manage market volatility, whereas outsourcing partners are utilized for volume production, segmented by their quality capabilities. This study contributes to the literature by demonstrating that mixed sourcing is not merely a cost-saving tactic but a mechanism to manage supply chain heterogeneity. Full article

Second-hand clothing is increasingly promoted as a sustainable alternative to reduce the fashion industry’s environmental impact, yet evidence on why consumers purchase second-hand apparel remains fragmented across disciplines. This literature review synthesizes prior research to identify the main motivational drivers and inhibitors of second-hand clothing purchasing and to translate them into a coherent conceptual explanation. We reviewed and conceptually integrated the academic literature on second-hand apparel consumption, focusing on how studies define, operationalize, and relate sustainability concerns, economic value, uniqueness and identity motives, and socio-cultural influences to purchase intention and behavior. The reviewed evidence indicates that pro-environmental values often coexist with utilitarian and symbolic motives, while barriers frequently involve perceived risk (e.g., quality and hygiene), effort, and access constraints. Building on this synthesis, we propose an integrative model that organizes key antecedents and mechanisms leading to purchase intention and repeat purchasing, highlighting enabling conditions and boundary factors that may strengthen or weaken these relationships. This review consolidates dispersed findings, clarifies theoretical gaps, and provides a testable framework to guide future empirical research and managerial interventions aimed at scaling circular fashion adoption. Full article

Vietnam’s exports expanded dramatically from $14.5 billion in 2000 to $405 billion in 2024, elevating the country to the world’s 22nd largest exporter despite persistent global shocks. This paper introduces the application of the Causal Machine Learning Approach to Resilience Estimation (CLARE) to industry-level trade analysis, utilizing a comprehensive panel of 97 HS2 sectors from 2000 to 2024 (2425 observations) drawn from UN COMTRADE and WITS databases. We implement Double Machine Learning to estimate causal effects of the Global Financial Crisis (2008–2009) and COVID-19 pandemic (2020–2021) on export growth. Results reveal stark industry disparities: electrical machinery (HS85) exhibits exceptional resilience, fueled by 72% high-technology content and low product concentration, while knitted apparel (HS61) proves highly vulnerable. Fixed effect regressions substantiate core hypotheses: a 10-percentage-point increase in high-tech share elevates the resilience index by 0.031 points (approximately 4.1% relative to the sample mean); a one-standard-deviation reduction in product HHI (0.14 units) yields a 0.026-point gain (3.6% relative); and each additional FTA contributes 0.047 points (approximately 6.2% relative), with all estimates significant at conventional levels. Robustness encompassing alternative learners, detrended outcomes, and synthetic controls upholds findings. Policy recommendations center on accelerating high-tech global value chain integration—targeting semiconductors and electric vehicles—while optimizing CPTPP and EVFTA utilization (currently 35%) and mitigating US–China market concentration (45% of exports). These insights chart pathways for Vietnam’s Vision 2045 high-income ambition amid intensifying geopolitical and climate risks, providing a replicable framework for other export-reliant emerging economies. Full article

The global fashion industry, particularly in production-intensive markets like China, faces pressing environmental challenges due to low utilization rates of post-consumer textiles, positioning the upcycling of secondhand clothing as a pivotal issue for sustainable transformation. Based on the Theory of Planned Behavior (TPB), this study examines the drivers of corporate participation in secondhand clothing upcycling at the organizational level, with a focus on how corporate attitudes, subjective norms, and perceived behavioral control shape behavioral intention and actual practice. Using data from a survey of 408 Chinese apparel firms and analyzing it via structural equation modeling, the findings reveal that attitudes, subjective norms, and perceived behavioral control each exert a significant positive influence on upcycling intention, which in turn strongly predicts actual upcycling behavior; the model demonstrates good overall fit. Beyond confirming the explanatory relevance of TPB in organizational sustainability decision-making, this study also develops a practical “value–pressure–capability” framework through sub-dimensional analysis. According to this framework, corporate upcycling engagement is motivated by perceived economic and brand value, moderated by external pressures from industry norms and policy signals, and enabled through technological innovation and resource support that lower implementation barriers. The research offers an evidence-based theoretical and practical pathway for policymakers and industry stakeholders seeking to advance the circular fashion economy, with implications for similarly structured economies in East Asia. Full article

This study investigates the sustainability of competitiveness in the textile and apparel industry across Asia following the 2005 conclusion of the Agreement on Textiles and Apparel (ATC). It aims to evaluate how sectoral competitiveness is understood and maintained beyond cost savings alone. A systematic review of the literature was conducted using PRISMA 2020 guidelines, analyzing 48 peer-reviewed journal articles from reputable sources published between 2001 and 2024. The selection process involved multiple stages of screening and thematic categorization, focusing on individual country case studies, competitiveness measures, indicators, analytical frameworks, and methodological approaches. A Risk of Bias assessment was conducted using the Mixed Methods Appraisal Tool (MMAT) to evaluate the methodological quality of the included studies. The findings highlight seven strategic pillars for sustaining competitiveness in the textile and apparel industry: shifting toward higher value-added manufacturing; integration into Global Value Chains (GVCs); technological innovation; adaptability; supply chain collaboration and organizational networks; responsible manufacturing; and government support. Moreover, the review includes a Co-occurrence analysis of all seven pillars. The analysis shows that supply chain collaboration and organizational networks serve as central pillars, often combined with adaptability and technological innovation. These findings demonstrate that maintaining industrial competitiveness in the textile and apparel industry no longer depends solely on cost efficiency but increasingly relies on strategic capabilities, ecosystem collaboration, and institutional support. The study offers a comprehensive framework to enhance the long-term competitiveness of textile manufacturing, particularly in Asia, contributing to the broader literature on transforming industries to stay competitive. Full article

Bangladesh is one of the major global garment-sourcing hotspots. Sustainability has become a megatrend and is shaping the international apparel industry. Given that Bangladesh is one of the largest garment exporters, it is essential to investigate the current sustainability initiatives being developed within the Bangladesh garment industry. Therefore, this study investigated the types of sustainability practices currently adopted within the garment industry in Bangladesh by analyzing publicly available sustainability reports from 25 garment factories published between 2020 and 2021. Guided by the triple bottom line theory, this study revealed through content analysis that companies prominently highlight environmental and social sustainability efforts, while economic sustainability receives comparatively limited attention. These insights identify areas for improvement in the current sustainable practices of the Bangladesh garment industry. Industry professionals, scholars in academia, and other stakeholders may use the primary findings of this study to holistically devise and implement strategies for sustainability practices in the Bangladesh garment industry. Full article

Children’s skin is uniquely vulnerable, requiring specialised design solutions that transcend traditional aesthetics. This exploratory study investigates the importance of paediatric dermatology in informing functional fashion design through expert medical perspectives. Using a qualitative approach, data were gathered from a purposive cohort of paediatric dermatologists and immunoallergologists and analysed through inductive thematic analysis. Findings identify four core themes: the physiological immaturity of children’s skin (notably the prevalence of atopic dermatitis), clothing’s role as a symptomatic aggravator rather than a primary aetiology, the clinical risks posed by chemical additives in synthetic textile processes, and the therapeutic potential of natural fibres and biofunctional agents. The data also highlights significant diagnostic constraints in paediatric patch testing, emphasising the necessity of proactive material safety. The findings suggest that integrating healthcare expertise into human-centred design may support the development of safer paediatric clothing solutions, ensuring that fashion industry innovation meets the physiological requirements of children. By transitioning from hazardous synthetic processes to biocompatible textiles, such as undyed natural fibres and medicinal plant-derived dyes, the industry can transform apparel from a potential irritant into a secondary protective barrier. This provides initial insights for developing clothing that safeguards the skin barrier and improves the overall wellbeing of vulnerable populations. Full article

Textile materials represent a versatile class of engineering substrates widely used in apparel, domestic products, and medical protective systems. Despite their extensive application, large-scale textile production has seen limited integration of fundamentally new functionalization strategies. In recent years, however, advances in materials science have enabled the development of textiles with tailored electrical, adaptive, and biological functionalities. This review summarizes recent progress in the functionalization of textile materials with a focus on approaches relevant to engineering and industrial implementation. Particular attention is given to conductive textiles designed for operation under extreme environmental conditions, including low-temperature climates. Methods for integrating electrically conductive elements into fibrous structures are discussed, highlighting their potential for sensing, thermal regulation, and energy-related applications such as powering portable electronic devices. Inkjet printing is presented as a scalable technique for high-resolution deposition of conductive patterns while preserving the mechanical integrity and aesthetic properties of textile substrates. In addition, adaptive and stimuli-responsive textile systems are reviewed, including materials capable of responding to thermal, optical, or chemical stimuli, with applications in camouflage, wearable systems, and multifunctional surfaces. The review further addresses the development of bioactive textiles, emphasizing antibacterial functionalization using organic and inorganic agents to mitigate the spread of pathogenic microorganisms. The relevance of such materials has been underscored by recent global viral outbreaks. Overall, this work aims to provide a materials science perspective on emerging textile functionalization strategies and to facilitate the transition of these technologies from laboratory-scale research to practical engineering applications. Full article

In the ready-to-wear industry, accurate estimation of fabric consumption is essential for cost efficiency, particularly for bias tapes, which constitute a notable share of overall material usage. Although bias tape is widely used across the apparel industry, no formal mathematical model exists for calculating its consumption, and current practices rely heavily on technician experience and sample garments. Because bias tape consumption in multi-size garment manufacturing involves geometric adjustments and decision steps that are not captured by existing methods, this study develops the first mathematically structured model for bias tape estimation and implements it in a software tool, providing a more reliable and standardized alternative to manual calculations. The model was validated using data collected in a real production environment from 20 garment models (13,122 units), and statistical analyses confirmed that the software produced significantly more accurate estimates than conventional methods, resulting in fabric savings of up to 39.5%. These findings demonstrate that the system enhances material utilization and supports data-driven planning in apparel manufacturing. Full article

This study explores how small and micro fashion and apparel enterprises (SMFAEs) conceptualize and structure social and environmental responsibility within an industry characterized by fragmented supply chains and limited institutional guidance. A qualitative, exploratory case study design examined four Québec-based enterprises through semi-structured interviews; these were analyzed using a hybrid thematic approach interpreted through stakeholder and legitimacy theories. The findings reveal three interdependent dimensions of responsible entrepreneurship: foundational commitments rooted in personal values; organizing mechanisms combining formal tools and informal learning to support continuous improvement; and contextual constraints related to sourcing and systemic opacity. The study advances understanding of early-stage responsibilization as a dynamic alignment between conviction, method, and feasibility. It contributes an integrative model that reframes sustainability from a compliance-oriented goal to an adaptive practice grounded in dialogue and learning. This perspective shows that meaningful sustainability emerges not from universal standards alone but from strengthening everyday human-scale processes of collaboration and adaptation. Full article

In the modern era, demand forecasting enhances the decision-making tasks of industries for controlling production planning and reducing inventory costs. However, the dynamic nature of the fashion and apparel retail industry necessitates precise demand forecasting to optimize supply chain operations and meet customer expectations. Consequently, this research proposes the Formicary Zebra Optimization-Based Distributed Attention-Guided Convolutional Recurrent Neural Network (FZ-DACR) model for improving the demand forecasting. In the proposed approach, the combination of the Formicary Zebra Optimization and Distributed Attention mechanism enabled deep learning architectures to assist in capturing the complex patterns of the retail sales data. Specifically, the neural networks, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), facilitate extracting the local features and temporal dependencies to analyze the volatile demand patterns. Furthermore, the proposed model integrates visual and textual data to enhance forecasting accuracy. By leveraging the adaptive optimization capabilities of the Formicary Zebra Algorithm, the proposed model effectively extracts features from product images and historical sales data while addressing the complexities of volatile demand patterns. Based on extensive experimental analysis of the proposed model using diverse datasets, the FZ-DACR model achieves superior performance, with minimum error values including MAE of 1.34, MSE of 4.7, RMS of 2.17, and R² of 93.3% using the DRESS dataset. Moreover, the findings highlight the ability of the proposed model in managing the fluctuating trends and supporting inventory and pricing strategies effectively. This innovative approach has significant implications for retailers, enabling more agile supply chains and improved decision making in a highly competitive market. Full article

The digitalization of business activities is already a reality in most developed countries. India, driven by strong information technology, is rapidly digitalizing across business industries. In the retail industry, this shift is visible in the adoption of omnichannel strategies to enhance value for customers, loyalty and trust, retailer’s image, overall shopping experience, and operational productivity. The present study assesses the extent of omnichannel transformation in the five leading Indian retail sectors viz. Consumer Electronics, Fashion and Apparel, Furniture and Home Decor, Grocery and Supermarkets, and Personal Care and Hygiene. The research design uses mystery shopping approach to collect data from 166 nationally present retailers to analyze their level of omnichannel implementation and digital adoption. The authors performed all statistical analyses and visualizations in R using the ggstatsplot package. The results highlight a less-than-ideal picture of channel integration, suggesting that while top retailers in each sector dominate channel integration, most others have made limited progress. Among the sectors, the Furniture and Home Decor sector leads in channel integration. Other contributions of this study include the enhancement of the existing measuring tool by introducing new indicators. The study reveals gaps in omnichannel implementation to help managers plan strategic improvements. Full article

This study analyzes how sustainability research in the textile and apparel industry is structured and argues that technological innovation—while essential for sustainable transformation—cannot generate meaningful impact when pursued in isolation. Its effectiveness depends on alignment with environmental assessment, ethical and institutional mechanisms, and circular strategies. A review of 133 publications (2020–2024) examining titles, keywords, abstracts, and conclusions identified these four thematic axes as the core framework shaping current research. Findings show that technological innovation is the most extensively addressed dimension, yet its industrial and policy influence remains limited when not connected to standardized assessment tools, governance systems, or consumer use-phase behaviors. When the four dimensions operate collectively, technological advances achieve stronger empirical validation, institutional coherence, and circular-system integration. By addressing a key gap in prior literature—which has typically examined these dimensions separately rather than as an integrated system—this study clarifies how their coordinated interaction conditions sustainability transition pathways. The integrated framework provides a theoretical basis for understanding constraints and mediators within sustainability transitions and suggests that future research and policy should adopt system-level strategies that intentionally strengthen linkages across the four dimensions to accelerate sustainable transformation. Full article

The apparel industry plays a critical role in the global economy but continues to face persistent challenges related to fit accuracy, overproduction, inefficiencies, and limited digital integration. These issues are particularly evident in made-to-measure (MtM) manufacturing, where manual processes, fragmented digital tools, and weak data continuity hinder scalability and sustainability. This study aims to identify the key barriers to MtM 4.0 adoption and propose a digitally integrated workflow capable of supporting efficient, sustainable, and customer-centric apparel production. A systematic review of Industry 4.0 technologies and MtM practices is conducted to structure the problem and derive the requirements for a next-generation workflow. Based on these insights, a three-stage MtM 4.0 workflow (connecting design, product development, and production) is developed and operationalized in a functional prototype, MtM Lusitano 4.0. The prototype integrates a web configurator, a rule-based pattern engine, and ERP/MES connectivity, enabling full digital continuity from customer input to shop-floor execution. Results from industrial deployment confirm functional improvements, including increased measurement accuracy, reduced manual interventions, and stable production release flows. The study concludes that the proposed MtM 4.0 workflow strengthens operational efficiency, supports sustainability goals, and provides a structured pathway for digital transformation in the apparel sector. Full article

This study investigates the impact of social media marketing activities on customers’ behavioral engagement with fashion clothing brands in Pakistan. Drawing on the Stimulus–Organism–Response (S–O–R) framework, this study examined how social media marketing activities affect brand love and subsequent consumers’ behavioral engagement, and to what extent gender moderates the association between social media marketing activities and brand love. Data were collected through a cross-sectional survey using convenience sampling, resulting in 297 valid responses. Partial Least Squares Structural Equation Modeling using SmartPLS 4 software was employed for the data analysis. The findings revealed that social media marketing activities have a substantial impact on brand love, and brand love, in turn, influences customers’ behavioral engagement. Specifically, social media marketing dimensions, such as entertainment, trendiness, customization, and word of mouth, emerged as statistically significant drivers of brand love, whereas interaction did not exhibit any effects. Furthermore, brand love also serves as a predictor of behavioral engagement. Regarding the moderating role of gender, the results confirm that the effect of customization on brand love is higher for females than for males. Similarly, gender acts as a moderator, indicating that the effect of word of mouth on brand love is stronger for males than for females. This study contributes to the literature by emphasizing the significance of brand love in formulating strategies to enhance consumer engagement in the digital landscape. Full article