The following paper assesses the relationship between electricity consumption, economic growth, environmental pollution, and Information and Communications Technology (ICT) development in Kazakhstan. Using the structural equation method, the study analyzes panel data gathered across various regions of Kazakhstan between 2014 and 2022. The data were sourced from official records of the Bureau of National Statistics of Kazakhstan and include all regions of Kazakhstan. The chosen timeframe includes the period from 2014, which marked a significant drop in oil prices that impacted the overall economic situation in the country, to 2022. The main hypotheses of the study relate to the impact of electricity consumption on economic growth, ICT, and environmental sustainability, as well as ICT’s role in economic development and environmental impact. The results show electricity consumption’s positive effect on economic growth and ICT development while also revealing an increase in pollutant emissions (emissions of liquid and gaseous pollutants) with economic growth and electricity consumption. The development of ICT in Kazakhstan has been revealed to not have a direct effect on reducing pollutant emissions into the environment, raising important questions about how technology can be leveraged to mitigate environmental impact, whether current technological advancements are sufficient to address environmental challenges, and what specific measures are needed to enhance the environmental benefits of ICT. There is a clear necessity to integrate sustainable practices and technologies to achieve balanced development. These results offer important insights into the relationships among electricity consumption, technology, economic development, and environmental issues. They underscore the complexity and multidimensionality of these interactions and suggest directions for future research, especially in the context of finding sustainable solutions for balanced development.

Building upon the cognition-affect-behavior model, this research aims to investigate the effect of greenwashing on consumers purchase intentions by testing the mediating effect of perceived betrayal and the moderating effect of brand loyalty. Data was collected through a questionnaire from 339 Chinese consumers involved in the fashion industry. AMOS 24 was employed to test the fitness of the proposed model, and the proposed hypotheses were tested through hierarchical regression analysis using SPSS 23. The results indicate that greenwashing has a negative impact on consumer purchase intentions, with perceived betrayal partially mediating this relationship. Additionally, the findings show that brand loyalty can mitigate the adverse effects of greenwashing on consumer purchase intentions. The findings of this study enhance the existing knowledge on the relationship between greenwashing and consumer purchase intentions, particularly in the fashion industry, and have significant practical implications for companies in this sector aiming to increase consumer purchase intentions.

This study analyzes in a comparative way the psychological meanings that social science and basic science researchers assign to the term “research”. Using the Natural Semantic Networks technique with 127 participants from a Colombian public university, we sought to unravel the distinctive epistemological and methodological positions between these disciplines. The findings reveal that, although both groups closely associate research with knowledge, they differ in the lexical network and associated terms, reflecting their different epistemological approaches. Basic science researchers emphasize terms such as “innovation” and “experimentation,” while social science researchers lean toward “solving” and “learning.” Despite the variability in the associated words, “knowledge” remains the common core, suggesting a shared basis in the perception of research. These results show the importance of considering disciplinary differences in research training and knowledge generation. The study concludes that research contributes significantly to both the advancement of individual disciplines and social welfare, urging future research to explore these dynamics in broader contexts to enrich interdisciplinary understanding and foster cooperation in knowledge generation.

This study, drawing on the Knowledge-Based View (KBV) and Contingency Theory, explores how analyzer strategic orientation, learning capability, technical innovation, administrative innovation, and SME growth and learning effectiveness are interrelated. Analyzing cross-sectional data from 407 founders, cofounders, and managers of trade and service SMEs in Vietnam’s Southeast Key Economic Region through PLS-SEM, the research demonstrates that analyzer orientation positively impacts both technical and administrative innovation, thereby bolstering SME growth and learning effectiveness. However, learning capability does not significantly impact technical innovation or growth and learning effectiveness. Instead, learning capability negatively affects administrative innovation. Notably, technical and administrative innovations act as mediators between analyzer orientation and SME growth and learning effectiveness. The study provides practical insights tailored for SMEs navigating dynamic market environments like Vietnam, enriching theoretical understanding of SME strategic management within the trade and service sector.

In the rapidly evolving landscape of technological innovation, the safeguarding of Intellectual Property Rights (IPR) emerges as a critical factor influencing economic growth and technological advancement. This study, conducted in the context of organizations operating in the United Arab Emirates (UAE), meticulously explores the intricate dynamics between IPR awareness, enforcement, and their implications for information security practices. The research undertakes a thorough investigation with three primary objectives: a comprehensive examination of IPR awareness, an exploration of the relationship between IPR enforcement and information security practices, and an assessment of the impact of information sensitivity. To achieve these objectives, a sample population of 150 respondents from various sectors was engaged, employing a combination of survey instruments and robust statistical analyses. The findings of the study illuminate a strong positive correlation between IPR awareness and information security practices, underscoring the pivotal role of cultivating IPR awareness among organizations. Furthermore, the enforcement of IPR, intricately connected with a resilient legal framework, regulatory authorities, international agreements, and effective customs and border control measures, is identified as a significant influencer of information security practices. The study employs a statistical model that exhibits a high explanatory power, elucidating approximately 85.9% of the variance in information security practices. In conclusion, the research offers profound implications for organizations, policymakers, and stakeholders in the UAE, advocating for strategies such as education, legal and regulatory support, international collaboration, and robust access control mechanisms to fortify IPR awareness, enforcement, and information security practices. The integration of advanced tools such as the smart PLS software adds depth and reliability to the study’s analytical framework, contributing to its comprehensive insights.

The rapid advancement of artificial intelligence (AI) technology is profoundly transforming the information ecosystem, reshaping the ways in which information is produced, distributed, and consumed. This study explores the impact of AI on the information environment, examining the challenges and opportunities for sustainable development in the age of AI. The research is motivated by the need to address the growing concerns about the reliability and sustainability of the information ecosystem in the face of AI-driven changes. Through a comprehensive analysis of the current AI landscape, including a review of existing literature and case studies, the study diagnoses the social implications of AI-driven changes in information ecosystems. The findings reveal a complex interplay between technological innovation and social responsibility, highlighting the need for collaborative governance strategies to navigate the tensions between the benefits and risks of AI. The study contributes to the growing discourse on AI governance by proposing a multi-stakeholder framework that emphasizes the importance of inclusive participation, transparency, and accountability in shaping the future of information. The research offers actionable insights for policymakers, industry leaders, and civil society organizations seeking to foster a trustworthy and inclusive information environment in the era of AI, while harnessing the potential of AI-driven innovations for sustainable development.