SEGi University

Purpose The purpose of this study is to examine the influence of two pivotal brand stimulus factors brand personality and brand experience on brand loyalty and brand referral in the Muslim fashion branded garment sector. This study also explores the quasi-moderating roles of brand affection and brand involvement in shaping post-purchase behavioural outcomes. Design/methodology/approach This study used a survey questionnaire distributed offline and online via WhatsApp by using purposive sampling. A total of 252 valid responses were collected from Malaysian consumers who had purchased branded Muslim fashion garments, with the majority being females (69.8%), aged 20–49 years old (91.3%) and bachelor’s degree holders (59.9%). The sample size exceeded the minimum requirement suggested by G*Power analysis. The data were analysed using moderated regression analysis with SPSS version 27. Findings Brand personality positively influences brand loyalty, indicating that human-like brand traits that resonate with consumers’ cultural and religious self-concepts can foster deeper emotional bonds dan sustained loyalty. This highlights the strategic importance of crafting brand identities that reflect modesty, authenticity and self-expression in Muslim fashion. Next, while brand experience positively influenced brand referrals, it unexpectedly reduced brand loyalty, possibly because of heightened customer expectations. Therefore, brands should carefully balance creating memorable, high-impact experiences with setting realistic expectations to preserve loyalty. Both brand affection and brand involvement enhanced brand loyalty and referrals, while also reinforcing the link between brand experience and referral behaviour, signalling that emotional attachment and personal relevance serve as powerful levers for advocacy. Originality/value This study offers a more comprehensive model than previous research by integrating brand personality, experience, affection and involvement to assess their combined effects on post-consumption behaviours. This study offers new theoretical and practical insights, advancing our understanding of consumer–brand dynamics in the Muslim fashion industry.

Purpose This study examines how intellectual capital components – human, structural, relational and renewal capital (RNC) – impact service innovation performance (SIP) in Chinese management consulting firms. It also investigates the mediating role of dynamic capabilities (DCs) in transforming intellectual capital into innovative service outcomes. The research aims to provide a comprehensive understanding of how consulting firms can strategically leverage their intangible resources and organizational capabilities to sustain a competitive advantage in a rapidly evolving market. Design/methodology/approach The study employs a quantitative research design using survey data from Chinese management consulting firms. Structural equation modeling is utilized to test relationships between intellectual capital dimensions, DCs and SIP. The analysis focuses on the direct effects of human, structural, relational and RNC on innovation, as well as the mediating effect of DCs. This empirical approach integrates theories from the resource-based view (RBV), enterprise capability theory and service innovation literature. Findings Results indicate all four intellectual capital components positively and significantly influence service innovation, with RNC exerting the strongest effect. DCs mediate these relationships by enabling firms to sense opportunities, seize them and reconfigure resources effectively. Human capital (HC) fosters creativity; structural capital supports knowledge management; relational capital enhances client collaboration and RNC drives continuous learning and adaptability. The findings confirm that strategic orchestration of intellectual capital through DCs is essential for sustaining innovation in consulting services. Research limitations/implications The study is limited by its focus on Chinese consulting firms, which may restrict generalizability to other cultural or industry contexts. The cross-sectional design limits causal inferences, suggesting longitudinal studies for future research. Measurement of intellectual capital and DCs relies on self-reported data, which may introduce bias. Further research could explore sector-specific variations, incorporate qualitative insights and examine external environmental factors influencing the intellectual capital innovation relationship. Despite limitations, the findings offer valuable insights for theory development and practical innovation management in knowledge-intensive service industries. Practical implications Consulting firms should invest in targeted HC development, advanced knowledge management systems and robust client relationship management to drive service innovation. Emphasizing continuous learning and renewal through research and development, foresight activities and collaborative partnerships is critical. Firms must enhance DCs by adopting agile project management and digital tools to quickly sense, seize and reconfigure resources. An integrated innovation strategy combining intellectual capital development with capability building helps firms remain competitive and responsive to rapid market changes. These practices foster sustained innovation, improved client satisfaction and organizational resilience. Social implications By enhancing service innovation, consulting firms contribute to more effective and customized solutions for client organizations, potentially improving overall business performance and economic growth. The promotion of continuous learning and talent development supports workforce skill advancement and knowledge diffusion within the industry. Trust-based client relationships foster transparency and collaboration, encouraging ethical business practices. Additionally, innovation driven by intellectual capital and DCs can lead to sustainable consulting services that better address complex societal challenges. These outcomes collectively promote a knowledge-based economy and strengthen the social fabric of professional service ecosystems. Originality/value This study uniquely integrates intellectual capital theory, DCs and service innovation theory to offer a holistic framework explaining innovation performance in consulting firms. It empirically validates the mediating role of DCs in converting intellectual capital into service innovation, extending the RBV with capability orchestration. By focusing on the Chinese management consulting context, the research provides culturally relevant insights into intangible resource management. The multi-theoretical model advances academic understanding and offers actionable strategies for practitioners to enhance innovation through coordinated development of human, structural, relational and RNC alongside dynamic organizational capabilities.

Abstract As urban mental health challenges grow, understanding how green spaces promote psychological restoration during exercise is crucial for sustainable urban development. While vegetation volume is a known factor, the psychological mechanisms through which objective green exposure translates into restorative outcomes, especially in dynamic exercise contexts remain insufficiently explored. This study investigates the Xuanwu Lake jogging circuit in Nanjing, China, a representative urban green space. We integrated GIS-based Normalized Difference Vegetation Index (NDVI) remote sensing data with subjective psychometric scales to assess green exposure. A multi-layered analytical framework was employed, combining Partial Least Squares Structural Equation Modeling (PLS-SEM) to test predictive relationships and Necessary Condition Analysis (NCA) to identify the minimum thresholds (bottlenecks) required for restoration. The findings reveal that subjective green exposure (Perceived Vegetation Density and Perceived Green Enclosure) significantly enhances psychological restoration by mediating dimensions of "Being Away" and "Fascination." Notably, Environmental Compatibility emerged as the strongest predictor, indicating that the alignment between the environment and the exerciser's needs is the primary driver of restoration. Furthermore, Nature Connectedness (NC) significantly moderates the relationship between green exposure and perceived restorativeness; individuals with higher NC are more sensitive to vegetation density. NCA results confirm that specific restorative dimensions function as "necessary but not sufficient" conditions, with compatibility and fascination acting as critical bottlenecks for high-level restoration.

The green transformation toward sustainable development poses significant challenges for the textile industry, particularly for Small and Medium-Sized Textile Enterprises (SMTEs) involved in resource-intensive chemical operations such as the dyeing and finishing of cotton yarn and fabrics. These firms often face financing gaps for upgrading textile mills, machinery, and equipment, which is critical for processing both natural and synthetic fibers. This study proposes an integrated decision-support framework, merging Multi-Criteria Decision Analysis (MCDA) and Monte Carlo simulation, to evaluate and prioritize green investments in textile processing technology. An evaluation of three retrofit plans identified that a comprehensive switch to waterless digital-printing equipment—a key advancement in textile technology—is the optimal solution for processing fiber products with minimal water and organic compound usage. A hybrid financing structure was optimized to fund the acquisition of this new equipment, and a digital Green Investment and Risk Coordination System (GIRCS) was designed for real-time risk tracking. The findings offer a replicable methodological blueprint for investment appraisal in the textile industry, aiding firms across the supply chain—from weaving to finishing—and contributing a novel approach at the intersection of materials science and engineering management.

Printed Circuit Board (PCB) defect inspection is critical in electronics manufacturing, yet annotating large training sets is labor-intensive and costly. This paper proposes a semi-supervised PCB defect detection framework based on YOLOv5, which leverages a small labeled dataset and a larger pool of unlabeled images through an iterative self-training pipeline. A YOLOv5 detector is first trained on the limited labeled data, then used to generate pseudo-labels on unlabeled images; high-confidence detections are retained as defect annotations, and the model is retrained on the combination of labeled and pseudo-labeled data. This pseudo-labeling and retraining cycle is repeated for multiple iterations to progressively refine the detector. The approach is evaluated on a PCB defect dataset with 100 labeled and 1,000 unlabeled images, and shows significant gains over a fully supervised baseline. The proposed semi-supervised YOLOv5 achieves 91.6% mAP@0.5 with only 100 labeled images, outperforming both the baseline (87.0% mAP) and prior semi-supervised methods, while substantially improving recall and precision. The results demonstrate that the method effectively reduces annotation effort while maintaining high detection accuracy, providing a simple, confidence-thresholded self-training strategy for deploying PCB defect detectors under limited labeling resources. This work directly supports SDG 9 by enabling cost-efficient, high-accuracy AI-based PCB inspection that strengthens intelligent and sustainable manufacturing systems.

Digital transformation is reshaping educational systems worldwide, creating new challenges for school leadership and organizational sustainability. However, existing research often examines digital leadership, teacher well-being, and school performance separately, leaving limited theoretical understanding of their integrated relationships. This study proposes a conceptual framework linking digital leadership, teacher well-being, and sustainable school performance. Drawing upon leadership and motivation theories, the framework suggests that digital leadership influences school sustainability both directly and indirectly through teacher well-being. The study highlights the importance of human-centered leadership practices in managing technological change and sustaining institutional performance. The proposed model offers theoretical guidance for future empirical studies and provides practical implications for educational leaders seeking to balance digital innovation with teacher support to achieve long-term school development.

BackgroundCircadian rhythm, the body's internal clock, synchronises with the 24-h light-dark cycle and is influenced by environmental cues such as light exposure and meal timing. Disruptions in this rhythm due to modern lifestyle factors, including irregular eating schedules, are linked to increased risks of cardiometabolic diseases. Time-restricted eating (TRE), which limits food intake to an 8-12 h window, often aligns with daytime (diurnal) eating and supports circadian alignment. In contrast, nocturnal TRE patterns, such as during Ramadan, may disrupt this rhythm by shifting food intake to nighttime.AimTo conduct a systematic review and meta-analysis evaluating the differential impacts of diurnal and nocturnal TRE on cardiometabolic health and circadian rhythm in healthy adults.MethodsThis review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and is registered with PROSPERO (CRD42023374947). A comprehensive search will be conducted using PubMed, Web of Science and Scopus. Two independent reviewers will screen titles, abstracts and full texts, extract data using a standardized form and assess risk of bias. Qualitative and quantitative (meta-analysis) synthesis will be conducted where appropriate.SummaryThis protocol outlines the methodology for synthesising current evidence on the differential effects of diurnal versus nocturnal TRE patterns. The findings will inform future dietary interventions aimed at optimising cardiometabolic health through circadian-aligned nutrition strategies.

Abstract Immobilized iron–copper nanoparticles (iFeCu) treated sewage effectively, and the treated effluent complies with Malaysia's effluent discharge standards. The good stability and reusability of iFeCu demonstrate its potential as an alternative to existing sewage treatment methods, which rely on microbial activity. However, no risk assessment has been conducted to evaluate the safety aspects of this method for real‐life applications. The objective of this study is to assess the safety of using iFeCu for sewage treatment in a pilot‐scale study. The risk analysis was carried out through the development and evaluation of hazard identification (HAZID), hazard analysis (HAZAN), and hazard and operability analysis (HAZOP). In a pilot‐scale continuous flow reactor (10 PE, flow rate 210–1200 mL/min, retention time 0.69–3.97 h), iFeCu achieved stable pollutant removal over 10 reuse cycles, with average removal efficiencies of 85%–95% for ammonia, 80%–90% for biochemical oxygen demand (BOD), and 60%–70% for chemical oxygen demand (COD). HAZID and HAZAN identified NaBH 4 as the highest‐risk chemical (severity 5, R = 15), while nanoparticle inhalation and Na 2 CO 3 spillage were medium‐risk hazards ( R = 8), both reduced to low risk after mitigation ( R = 2). Periodic maintenance of equipment and daily sewage quality monitoring minimizes the likelihood of flow, reaction, and level hazards. Emergency measures, such as emergency shutdowns and bypassing damaged components, were proposed to manage potential incidents. In conclusion, the risk assessment of using iFeCu for sewage treatment indicates that it is safe, and the recommended mitigation steps further enhance the practicality of this method for real‐life applications.