The educational-instructional process, specific to the preschool age of 4–5 years, is oriented towards the formation of children’s motor and cognitive skills. As part of physical activities in preschool education, various exercises are performed to strengthen motor and verbal responses. Light physical exercises and movement games are used to improve motor skills and verbal ability. The present research was carried out on a group of 20 preschoolers, using an experimental methodology, with the help of One-Group Pre-test and Post Test Design. Based on the statistical analysis of the data obtained from the motor skills evaluation tests and the cognitive skills evaluation tests, the value p < 0.001 indicates a positive statistical significance between the pre-test and the post-test. The values of Cohen’s D coefficient by which the effect size was evaluated indicate its great influence (D = 0.893). In conclusion, the differences between the pre-test and post-test values show significant progress, which underlines the effectiveness of the intervention aimed at improving motor and cognitive skills in preschoolers.

The financial services industry is experiencing a swift adoption of artificial intelligence (AI) and machine learning for a variety of applications. These technologies can be employed by both public and private sector entities to ensure adherence to regulatory requirements, monitor activities, evaluate data accuracy, and identify instances of fraudulent behavior. The utilization of artificial intelligence (AI) and machine learning (ML) has the potential to provide novel and unforeseen manifestations of interconnectivity within financial markets and institutions. This can be represented by the adoption of previously disparate data sources by diverse institutions. The researchers employed convenience sampling as the sampling method. The form was filled out over the period spanning from July 2023 to February 2024, and it was designed to be both anonymous and accessible through online and offline platforms. To assess the reliability and validity of the measurement scales and evaluate the structural model, we employed Partial Least Squares (PLS) for model validation. Specifically, we have used the software package Smart-PLS 3 with a bootstrapping of 5000 samples to estimate the significance of the parameters. The results indicate a positive and direct connection between artificial intelligence (AI) and either financial services or financial institutions. On the contrary, machine learning (ML) exhibits a strong and positive association among financial services and financial institutions. Similarly, there exists a positive and direct connection between AI and investors, as well as between ML and investors.

This research investigates the determinants of digital transformation among Vietnamese logistics service providers (LSPs). Employing the Technological-Organizational-Environmental framework and Resource Fit theory, the study identifies key factors influencing this process across different three stages: digitization, digitalization, digital transformation. Data from in-depth interviews with industry experts and a survey of 390 LSPs were analyzed using covariance-based structural equation modeling (CB-SEM). The findings reveal that the factors influencing the digital transformation of Vietnamese LSPs evolve across different stages. In the initial phase, information technology infrastructure, financial resources, employee capabilities, external pressures, and support services are key determinants. As digitalization progresses, leadership emerges as a crucial factor alongside the existing ones. In the final stage, the impact of these factors persists, with leadership and employee capabilities becoming increasingly important.

The purpose of this study is to investigate the relationship between the use of business intelligence applications in accounting, particularly in invoice handling, and the resultant disruption and technical challenges. Traditionally a manual process, accounting has fundamentally changed with the incorporation of BI technology that automates processes and allows for sophisticated data analysis. This study addresses the lack of understanding about the strategic implications and nuances of implementation. Data was collected from 467 accounting stakeholder surveys and analyzed quantitatively using correlational analysis. Multiple regression was utilized to investigate the effect of BI adoption, technical sophistication on operational and organizational performance enhancements. The results show a weak association between the use of BI tools and operational enhancements, indicating that the time for processing invoices has decreased. Challenges due to information privacy and bias were significant and negative on both operational and organizational performance. This study suggests that a successful implementation of a BI technology requires an integrated plan that focuses on strategic management, organizational learning, and sound policies This paper informs practitioners of how accounting is being transformed in the digital age, motivating accountants and policy makers to better understand accounting as it evolves with technology and for businesses to invest in concomitant advances.

Sustainability and green campus initiatives are widely examined in developed countries but less attention has been paid in developing countries such as Pakistan. Therefore, this study intends to examine the links between sustainability dimensions and green campus initiatives by mediating role of teachers and students’ involvement. Green campus or sustainable campus or environment friendly campus is based on the principles of environmental sustainability, incorporating social, and economic and environmental dimensions. Questionnaire for assessment of sustainability was adopted and 529 responses were received from the faculty, management and servicing staff of the seven Mountain Universities of the Gilgit Baltistan and Azad Jammu and Kashmir in Northern Pakistan. Partial Least Square Structural Equation Modeling (PL-SEM) was used to analyse the data. The results indicated that energy conservation, water conservation, green transport, sustainable waste management have enhanced campus green initiatives. Teachers and students’ involvement partially mediate the relationship between green transport strategies, sustainable waste management and green campuses initiatives. While on another hand, teachers and students’ involvement have not mediated the links between energy conservation, water conservation and green campus initiatives. The study contributes to theory building in the area of green and environment friendly campus initiatives by enriching the understanding of the processes carrying the effect of sustainability dimensions and both teachers and students’ involvement.

The study’s purpose is to evaluate the influence of some factors of the model of planned behavior (TPB) and the perceived academic support of the university on the attitude toward entrepreneurship and entrepreneurial intention of students. The results of Structural Equation Modeling (SEM) linear structural model analysis with primary data collected from 1162 students indicated that entrepreneurial intention is influenced by attitude toward entrepreneurship, subjective norm, perceived educational support, and perceived concept development support. In addition, this study also found the positive influence of perceived educational support, concept development support, and business development support on attitude towards entrepreneurship. Interestingly, the influence of perceived business development support on entrepreneurial intention was rejected, and personal innovativeness is demonstrated to promote an attitude toward entrepreneurship. Notably, this study also highlights the moderating role of personal innovativeness on the relationship between attitude toward entrepreneurship and entrepreneurial intention. Based on these findings, several implications were suggested to researchers, universities, and policymakers.