Despite great academic interest in global green supply chain management (GSCM) practices, its effectiveness for environmental management systems (EMS) and market competitiveness during COVID-19 remains untapped. Existing literature suggests that a fundamental link between GSCM, EMS, and market competitiveness is missing, as supply management is critical to maintain market competitiveness. To fill this gap in the literature, this study examines whether environmental management systems influence the link between GSCM practice and market competitiveness in China. We also propose the articulating role of big data analytics and artificial intelligence (BDA-AI) and environmental visibility toward these associations in the context of the COVID-19 pandemic. We evaluated the proposed model using regression-based structural equation modeling (SEM) with primary data (n = 330). This result provides empirical evidence of the impact of GSCM on EMS and market competitiveness. Moreover, the results show that the BDA-AI and the environmental visibility enhanced the positive relationship between GSCM-EMS and EMS and market competitiveness in China. Recent research shows that supply chain professionals, policymakers, managers, and researchers are turning to formal EMS, BDA-AI, and environmental visibility to help their organizations achieve the competitiveness that the market indicates they need.

Consumer loyalty in high-tech markets is challenged by rapid technological change and shifting consumer expectations. Although Consumer Perceived Value (CPV) research exists across various industries, studies on high-tech brand value perceptions in emerging economies, such as Sri Lanka, are limited. This paper examines the influence of brand value dimensions on consumer loyalty in Sri Lanka and provides practical insights. Primary data from 463 university students, collected via a Web-based survey, were analyzed using Statistical Package for the Social Sciences (SPSS) and Analysis of Moment Structures (AMOS). Structural Equation Modeling (SEM) was used to test the hypothesized relationships between macro-level brand associations, perceived value dimensions, and consumer loyalty outcomes. The results of the exploratory and confirmatory factor analyses confirmed the validity of the model, with 16 out of 18 hypotheses supported, demonstrating strong model fit and significant relationships. Macro-level brand associations had a varied but significant influence on brand value dimensions. Functional, social, and emotional values accounted for the most variance in loyalty constructs, while economic and epistemic values showed weaker effects. The findings of this research reinforce and refine the body of knowledge on the CPV concept in high-tech industries.