Renewable Energy Systems (RES) are increasingly recognized as a critical pathway to achieving Sustainable Development Goal 7 (SDG 7) in BRICS countries (Brazil, Russia, India, China, and South Africa), which aims to ensure access to affordable, reliable, sustainable, and modern energy for all. Despite rapid economic growth, these nations face significant energy challenges, including energy poverty, fossil fuel dependence, and environmental degradation. This study examines the application of renewable energy systems as a pathway to achieving Sustainable Development Goal 7 in BRICS+ countries. A scoping review was conducted to gain a comprehensive understanding of the subject, with a search from pertinent articles across various databases and search engines, including Scopus, EBSCO, ABI Inform, IEEE, PubMed, and Science Direct. The findings affirmed that BRICS countries (Brazil, Russia, India, China, and South Africa) are utilising renewable energy, although Russia is on a slow path to achieving this just energy transition. The findings also indicate that South Africa's Renewable Energy Independent Power Producer Procurement Program (REIPPPP) significantly contributes to diversifying the energy mix by attracting private sector investments in solar, wind, and other renewable sources. However, despite these efforts, South Africa remains heavily reliant on fossil fuels. It was also affirmed that China is rapidly expanding its solar and wind energy capacity and that the nation's leadership in renewable energy investment has significantly reduced its reliance on coal while increasing the availability of clean energy. The findings further affirmed that Brazil's considerable utilisation of biomass and hydroelectric power, which make up 32% and 12% of its energy mix, respectively, illustrates the potential for diversifying energy sources to minimise carbon footprints.

The adoption of digital payment systems is influenced by a range of factors, including individual attitudes, anxiety levels, self-efficacy, and age. The present study empirically examines the moderating role of attitude, anxiety, self-efficacy, and uncertainty about aging on the relationship between UTAUT model key determinants and older adults’ intention to use digital payment applications. A telephonic survey was conducted to collect data from 138 older adults across the Indian state of Tamilnadu. Study findings show that older adults with a positive attitude towards using technology believe that digital payment applications are likely to be useful and easy to use, whereas high anxiety levels consider it less likely to be useful. Uncertainty about aging did not show any significant impact over the key determinants of the UTAUT model on behavioural intention. Facilitating environments enhance the adoption of digital payment applications provided requisite facilities and support (technical and family) available to older adults. Low self-efficacy moderates the relationship negatively to performance expectancy and facilitating conditions on behavioural intention.

The purpose of this study was to examine the role of digital innovation in mediating the influence of organizational digital culture, digital leadership, and digital transformation on organizational performance in the Indonesian Army Hospital (Rumah Sakit TNI Angkatan Darat). The research employed Structural Equation Modeling (SEM) analysis, specifically Partial Least Squares Path Modeling (PLS-SEM), using SmartPLS 3.0 software for data analysis. The sample used in this study consisted of 123 respondents, all of whom were leaders of TNI AD Class/C Hospitals. The findings of this study indicated that digital leadership, digital transformation, and digital innovation all had a partial positive effect on organizational performance. Furthermore, digital transformation had a partial positive and significant effect on digital innovation. Meanwhile, organizational digital culture did not have a significant effect on either organizational performance or digital innovation. Additionally, digital leadership did not have a significant effect on digital innovation. Based on the mediation test conducted using the Sobel test, it was found that digital innovation only mediated the effect of digital transformation on organizational performance. However, digital innovation did not mediate the effect of organizational digital culture or digital leadership on organizational performance. The theoretical implications of this study contribute to the development of Resource-Based View (RBV) theory by emphasizing the importance of digital leadership, digital transformation, and digital innovation in achieving superior organizational performance. These findings provide valuable insights for researchers and practitioners who wish to leverage resources, digital leadership, digital transformation, and digital innovation to enhance organizational performance, especially amidst the growing business competition that increasingly relies on digital technology. However, the limitations of this study lie in the scope of the sample used, as the research sample was limited to leaders of Class/C TNI AD hospitals. Future research could consider expanding the population by using samples from different types of TNI AD hospitals.

Accounting and financial reports summarize the financial situation of companies and are essential for decision-making. Independent auditors verify this information, and the value of their fees is a point of interest in literature. This study analyzes the determining factors of audit fees for companies listed on B3. The research is quantitative, based on 182 companies listed between 2017 and 2020, using descriptive statistics, mean tests, regression with panel data and bootstrap. The results indicate that companies audited by BIG4 firms, which have larger audit committees and were part of the pandemic year tend to have higher costs. However, a greater number of members on the committee reduces costs. The bootstrap technique confirmed the consistency of the model estimators.

In recent years, the field of remote working has seen significant growth in research and practical implications, primarily influenced by the COVID-19 pandemic. The adoption of remote work has significantly influenced organizational practice and employee experience, leading to a number of published articles discussing these topics. The present study analyzes the development of research on remote work and its impact on employee engagement and productivity using bibliometric analysis. To comprehend and analyze the growing body of literature this study uses VOSviewer tool and Scopus database. A total of 969 publications were retrieved from Scopus database to explore research trend in this field. Utilizing the SCOPUS database, we examined 969 articles published in reputed journals in management, psychology, and social sciences from 2015 to 2024. In this study analyzed total citation, most cited publication, leading author and journal and national contribution. The research utilized descriptive analysis and science mapping methods to provide meaningful insights for researchers, pinpointing key foundational works and collaborative networks. The result provided a clear understanding of current research and indicated potential areas of future study. Future research is encouraged to broaden the scope and utilize additional databases for a more comprehensive analysis.

This study examines the transformative role of AI in digital marketing, addressing gaps in novelty, theoretical depth, and methodological rigor highlighted in prior critiques. By introducing the Integrated AI Marketing Framework (IAMF), a synthesis of the Technology Acceptance Model (TAM) and Resource-Based View (RBV), the research offers fresh theoretical insights. Empirical data from 200 global firms and 30 expert interviews reveal that AI-driven strategies yield 30% higher ROI, 25% improved conversion rates, and 20% reduced acquisition costs compared to traditional methods. The framework also links AI adoption to 1.5x higher sustainability adoption and 40% revenue resilience during crises. Methodological improvements include comparative benchmarking and sampling adjustments to mitigate bias.

The emergence of e-commerce has brought about a dynamic shift in consumer shopping experiences, altering how consumers interact with fashion and apparel. The purpose of this study is to compare how customers shop for clothing and fashion through these two channels. It examines important elements including convenience, affordability, product variety, shopping experiences, and the return and exchange policy. The study also looks at how age, gender, and income level affect people's shopping preferences. The survey was administered through a structured Questionnaire. Analyzing the data collected using statistical tools like chi square, regression.

This research work has explored the moderating role of job satisfaction in the relationship between personality traits and organizational citizenship behavior (OCB) among academic staff employed in private arts and science colleges. The study rests on the foundation that the impact of dispositional variable (personality traits) in promoting organizational citizenship behavior depends upon the moderating influence of the attitudinal variable (job satisfaction). As citizenship behaviors are significant for enhancing organizational effectiveness, this work will help to know the predictive power of personality traits under the moderating influence of job satisfaction in promoting citizenship behaviors among teaching staff. The sample size for the study is 212 which was collected by convenience sampling technique. Data was analyzed by multiple regression using SPSS 28. The results supported the moderating influence of job satisfaction in the personality – organizational citizenship behavior relation.

In an era where digital transformation is redefining the fabric of workplaces, the emphasis on employee well-being has become central to strategic human resource management. Organizations are increasingly recognizing that the mental, emotional, and psychological wellness of employees is directly linked to productivity, innovation, retention, and overall organizational success. Traditional well-being assessment models are often reactive, relying on annual surveys and generic feedback mechanisms that fail to capture the nuances of evolving workforce needs. This paper introduces a proactive and data-driven framework using Artificial Intelligence (AI) and predictive analytics to enhance employee well-being, particularly in the dynamic environment of the Indian IT sector. The study is grounded in the application of a cluster-based segmentation model that categorizes employees into meaningful subgroups based on six core well-being dimensions: organizational culture, communication effectiveness, motivation, HR support, perception of being valued, and work-life balance. Drawing on empirical data collected from 258 IT professionals across Karnataka, the research applies K-means clustering to identify distinct well-being profiles. The optimal number of clusters was determined using the Elbow Method, resulting in the classification of respondents into High, Moderate, and Low Well-Being clusters. To statistically validate the segmentation, ANOVA tests were conducted across the six dimensions, revealing significant inter-cluster differences. Communication and organizational culture emerged as the most influential variables, with large effect sizes (Cohen’s d > 1.5), indicating their critical role in differentiating well-being levels. Chi-square tests were also performed to analyze the association between demographic variables and cluster membership, revealing significant associations particularly in relation to age group. Interestingly, younger employees (under 30) were more likely to be part of the Low Well-Being cluster, suggesting a generational shift in expectations and experiences at work. The findings highlight the utility of AI in developing personalized HR interventions that align with the unique needs of different employee segments. For instance, the High Well-Being cluster could be further engaged through leadership development and recognition programs, while the Low Well-Being group requires targeted support in communication and mental health. The cluster-based approach enables HR professionals to replace the outdated one-size-fits-all strategies with focused, data-informed practices. Beyond the empirical findings, this study contributes to the theoretical discourse on ethical AI usage in HRM. It emphasizes the need for transparency, data consent, and algorithmic fairness when deploying AI tools in people management. As AI increasingly becomes a staple in organizational decision-making, this paper advocates for a human-centric design that enhances, rather than undermines, employee welfare. In conclusion, this research offers a replicable, scalable model for integrating AI into HRM systems to support sustainable employee engagement and well-being. The methodological rigor and practical implications position this work as a valuable contribution to both academia and industry, especially as organizations prepare for future-ready, digitally empowered workforce ecosystems.