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Eco-innovation has emerged as a strategic mechanism for enhancing corporate sustainability, particularly in emerging African economies facing environmental and institutional pressures. Despite growing interest, empirical evidence explaining how eco-innovation translates into sustainable business performance remains limited. This study investigates the direct and indirect effects of eco-innovation on sustainable business performance, incorporating green competitive advantage as a mediating construct. Using survey data collected from 312 manufacturing and service firms across Nigeria, Kenya, and South Africa, the study applies Partial Least Squares Structural Equation Modeling (PLS-SEM). The results reveal that product, process, and organizational eco-innovation significantly enhance green competitive advantage and sustainable business performance. Furthermore, green competitive advantage partially mediates the eco-innovation–performance relationship. The findings contribute to eco-innovation literature in emerging economies and provide strategic implications for managers and policymakers.

The Affective AI Literacy Model (AALM) proposes that genuine AI literacy requires four integrated dimensions: Cognitive Decoding, Emotional Regulation, Ethical Discernment, and Technological Empathy. This article provides the first empirical corpus validation of the AALM by introducing the Affective AI Literacy Index (AALI), a computational metric measuring the proportion of empowerment markers in naturalistic learner-generated educational AI discourse, and identifies the Emotional Regulation Gap — the systematic under-representation of Agency markers relative to all other AALM dimensions in current educational AI discourse. A corpus of 829 YouTube comments was collected via the YouTube Data API v3 across five educational AI discourse domains (April 2026). Python-based lexical annotation applied marker patterns across six categories — Understanding, Agency, Ethics, Collaboration, Anxiety, and Rejection — grounded in Goleman (1995), Vygotsky (1978), Selwyn (2021), and the AALM framework. The AALI was computed as empowerment markers divided by total markers. The full corpus is deposited at Zenodo (DOI: 10.5281/zenodo.19519080). The mean AALI is 0.8861, confirming that educational AI discourse is substantially empowerment-dominant. However, the dimension distribution reveals a critical structural imbalance: Cognitive Decoding dominates (0.7041 per 100 tokens; 59.7% of empowered comments), while Emotional Regulation is the least represented dimension (0.0940 per 100 tokens; 8.4% of empowered comments). Domain-level analysis shows that AI ethics content produces the highest AALI (0.9621) and AI anxiety/future jobs content produces the lowest (0.6609) — confirming that fear-framed educational discourse activates resistance rather than empowerment. The AALI is the first computational instrument for measuring Affective AI Literacy in naturalistic educational discourse. The Emotional Regulation Gap is an original empirical finding with direct curriculum design implications: current AI

and dependences. Parents often play a crucial role in adults’ life by providing support and guidance. Students’ poor wellbeing is a serious concern in universities. Mental health problems are associated with a range of study-related problems including lowered academic achievement and cognitive performance. Problems in student well-being such as prolonged stress may lead to burnout. Thus, the present study is entitled as “The Effect of Helicopter Parenting on Emerging Adult Students Burnout” is an attempt to seek the relationship between Helicopter Parenting and Burnout of Emerging Adult students studied at higher education institutions of Odisha and to find out the significance difference in the level of Helicopter Parenting and Burnout among higher students on the basis of locality and gender of Emerging Adult students studying in higher education institutions of Odisha. So, for this the Cor-relational method was adopted for the study. This research uses a quantitative approach with cor-relational analysis and T-Test. The study concluded that high level of perceived Helicopter Parenting in rural adults could be possibly due to the collectivistic nature of people, where decisions are taken based on the approval of parents and parents actively take interest in their child’s life which may hinder the child’s autonomy.

Teachers now use digital tools to improve their teaching methods which results in better student learning and teaching outcomes. The extended duration of teachers’ technology use will create new health problems which teachers must address. The study evaluates how Smart Board usage affects teachers’ health through research conducted with 150 educators from different age groups. The study shows that digital teaching methods can cause serious health threats which develop after extended periods of use. About 74.7 percent of teachers experienced high stress levels while 62.0 percent suffered from serious visual discomfort and 56.7 percent endured extreme body pain. The daily Smart Board usage results in strong visual strain and stress level increases according to the study which found statistical connections between these variables. The research results demonstrate that people who use Smart Boards more than five hours every day will experience their health symptoms start to intensify. The study shows that younger teachers use more visual resources than older teachers while older teachers deal with greater body pain from their seating position and body movement. The study demonstrates that educational technology implementation will lead to health consequences for students and teachers. Educational institutions must establish ergonomic standards and usage policies and wellness programs to ensure Smart Board technology benefits teaching while protecting teacher health.

This study examines the effect of changing work environment on employees’ job satisfaction for sustainable development using job characteristics model. The author examine the effects of work-family conflict and networking of the employees in the relationship between changing work environment and their satisfaction towards their job for sustainable development. The study employed descriptive and causal comparative research design and followed the judgmental sampling technique for data collection from the employees based on their service performance. Respondents were gathered from the aspiring professionals and data were collected from 384 employees. The factors such as skill variety, task identity, autonomy showed a high degree of significant relationship between changing work environment and employees job satisfaction whereas the role of networking relationship with both internal and external parties has also made a high degree of significant impact on the employees’ job satisfaction for sustainable development. Results have also shown that the task significance and feedback has shown a slight low impact on employee job satisfaction. The role of work-life conflict showed the negative impact on employee job satisfaction. Maintaining a perfect balance between work and family is considered quite difficult for current employee. Long work hours, heavy work demands, work role ambiguity and job distress have been positively linked to work-family conflict. This study contributes to the work-life conflict and its relevance in the changing work environment at work for motivating staffs at workplace based on the Job Characteristics Model (JCM) as a contemporary theory of motivation to fulfill the gaps in the empirical research in developing countries.

Smart Energy Management Systems (SEMS) are truly transforming how we think about energy use, allowing us to reduce carbon emissions and foster sustainability in our modern world. As global electricity demand is expected to soar by an incredible 50% by 2050 as per International Energy Agency, innovative technologies—like Artificial Intelligence (AI), the Internet of Things (IoT), blockchain, and big data analytics—are playing a pivotal role in creating intelligent, decentralized energy networks. But SEMS goes beyond just efficiency; it’s a catalyst for attaining the United Nations Sustainable Development Goals (SDGs), promoting sustainable economic growth while bolstering the resilience of our energy grids and expanding renewable energy adoption. In an era of rapid technological advancements and growing environmental concerns, energy management has become a critical challenge. Smart Energy Management Systems (SEMS) by changing how energy is generated, controlled, and used. Through AI integration, SEMS gain the ability to monitor operations in real time, utilize predictive insights, and execute automated control measures. These capabilities significantly enhance efficiency and help reduce the overall environmental

Digital opinion leaders have emerged as powerful actors within contemporary consumer ecosystems, shaping attitudes, preferences, and purchasing behaviors through social media interactions. While traditional advertising relies on institutional credibility, digital opinion leaders influence audiences through perceived authenticity, interpersonal trust, and psychological identification. This article examines how digital opinion leaders affect brand attitudes among Polish Millennials and Generation Z consumers through the lens of consumer psychology. By integrating theories of social identity, trust formation, parasocial interaction, and cognitive processing, the paper explores the psychological pathways through which influencer-generated content impacts consumer evaluations of brands. Particular attention is given to generational differences in information processing, emotional engagement, and digital trust. The analysis reveals that Gen Z consumers are more likely to develop emotionally driven brand perceptions through parasocial attachment, whereas Millennials demonstrate stronger reliance on expertise, informational quality, and perceived credibility. The findings contribute to understanding how digital influence mechanisms operate within emerging European consumer markets and provide implications for ethical digital marketing practices.

Blockchain technology offers powerful solutions to one of higher education’s most persistent challenges: the cumbersome and fraud-prone process of credential verification. Traditional methods of authenticating academic certificates are slow, manual, and resource-intensive. Blockchain promises to solve this by creating a secure, decentralized, and immutable digital ledger, enabling instant and permanent verification of degrees and academic credits, independent of the originating institution. Despite its promise, implementing blockchain in higher education introduces a series of complex technical, organizational, and regulatory challenges. The most immediate barriers are technical and financial — decentralized academic networks require advanced digital infrastructure and skilled IT professionals that many universities lack. High computational power and energy consumption raise significant sustainability concerns. Systemic and data-governance issues present further hurdles, most notably the lack of standardized protocols across diverse educational ecosystems. Privacy regulations such as GDPR conflict directly with blockchain’s immutability principle. Furthermore, the scarcity of qualified blockchain developers and resistance among institutional stakeholders continue to impede adoption. This paper systematically reviews the core features and processes of blockchain technology, its benefits for higher education, and the multifaceted challenges that must be addressed for successful implementation. A synthesis of current blockchain applications in education is presented alongside a discussion of emerging solutions, supported by comparative dataset analysis. The review concludes with actionable recommendations for institutions, policymakers, and researchers to facilitate a responsible and scalable transition toward blockchain-enabled academic ecosystems.

The rise of social media influencers has transformed digital communication, marketing, and consumer behavior. Influencers occupy a unique position between celebrities and peers, enabling them to shape opinions, purchasing decisions, lifestyle preferences, and social attitudes across diverse audiences. However, psychological responses to influencer content vary significantly among generations due to differences in media literacy, technological exposure, social values, and trust mechanisms. While younger generations often demonstrate higher levels of engagement and identification with influencers, older generations tend to exhibit greater skepticism and critical evaluation of sponsored content. This study examines the psychological dynamics underlying generational differences in responses to influencer content on social media platforms. Through an analysis of existing literature and theoretical perspectives, the paper explores admiration, trust, parasocial interaction, social comparison, skepticism, and consumer resistance across Generation Z, Millennials, Generation X, and Baby Boomers. The findings suggest that generational characteristics play a critical role in shaping perceptions of authenticity, credibility, and persuasive influence. The study contributes to understanding how social media marketing strategies can be adapted to diverse demographic groups while highlighting the psychological implications of influencer culture in contemporary digital society.

The rapid expansion of digital scholarly communication has intensified the demand for advanced, automated bibliometric systems capable of moving beyond simple counting exercises. Traditional bibliometrics remains limited in extracting semantic, contextual, and interdisciplinary insight from scholarly texts, relying instead on citation counts, h-index values, and co-authorship statistics that overlook the intent and quality of scholarly influence. Artificial Intelligence (AI), particularly Natural Language Processing (NLP), deep learning, and graph-based learning, enhances bibliometric evaluation by enabling citation intent classification, thematic trend analysis, semantic similarity mapping, and predictive scientometrics. This paper defines the objectives, operational boundaries, and ethical challenges associated with integrating AI into bibliometric research. It reviews contemporary literature, outlines a structured methodological approach built around transformer architectures, topic modelling, and network-based learning, and presents conceptual workflow visualizations. Ethical, technical, and computational considerations, including bias, transparency, reproducibility, scalability, and responsible use, are examined in depth. The study concludes by proposing principles for responsible AI-enabled bibliometrics suitable for research evaluation within Scopus-indexed academic environments and beyond, offering researchers, institutions, and policymakers a structured, balanced understanding of both the promise and the limitations of AI-driven scholarly assessment, while

The global publishing industry in India, which is one of the largest in the world, is going through rapid change as a result of the introduction of Knowledge Management (KM) practices. This case study looks at KM frameworks within academic, trade, and regional publishing, with a focus on digital repositories, the transfer of tacit knowledge, AI-powered editorial tools, and organizational learning. The evidence from the cases points out both the opportunities and the challenges involved, such as the difficulty of handling multiple languages, shortcomings in infrastructure, and resistance to change. The study includes a detailed analysis of Publications Hub in New Delhi, a medium-sized publishing consortium that has incorporated KM frameworks into its editorial and distribution processes. It is concluded that in order to maintain competitiveness and promote innovation in the Indian publishing sector, a strategic adoption of KM, backed by collaborative platforms and new technologies, is essential. Data gathered from 20 publishers that are part of the Hub show that KM practices—such as the use of digital repositories and peer review management systems, as well as the transfer of tacit knowledge via editorial mentorship—greatly improve operational transparency and cut down turnaround times. The case study makes it clear that for the purpose of sustaining innovation and competitiveness in Indian publishing, a strategic adoption of KM, supported by capacity building, collaborative platforms, and emerging technologies such as blockchain, is necessary. By treating Publications Hub as a representation of broader industry trends, the paper emphasizes the role of KM not only as a means of promoting organizational learning but also as a catalyst for digital transformation in India’s knowledge economy.