Online learning is one of the educational solutions for students during the COVID-19 pandemic. Worldwide, most universities have shifted much of their learning frameworks to an online learning model to limit physical interaction between people and slow the spread of COVID-19. The effectiveness of online learning depends on many factors, including student and instructor self-efficacy, attitudes, and confidence in using the technology involved; the educational strategies employed; the ability to monitor and evaluate educational outcomes; and student motivation, among many others. In this study, we analyzed how these factors were associated and impacted each other. We developed a comprehensive model after an extensive review of the relevant literature. The model was validated by applying partial least square regression to the data obtained by surveying 469 students who were enrolled in online education. The test results indicated that all the variables had a positive effect on the effectiveness of online learning. The effectiveness of online learning had a significant impact on the benefits of online learning. This showed that the more effective online learning was, the more benefits and positive outcomes the student experienced. The result of this research showed that learning objectives could enable universities to increase the effectiveness of students’ online learning by motivating students to join online classes and developing appropriate learning strategies for their individual needs.

Blockchain is considered one of the key technologies that can accelerate the Industrial Revolution 4.0. The intention to use Blockchain can still be improved in several ways, and how users perceive Blockchain is likely to be influenced by how well they understand the underlying theory. This study examines several important factors, namely government regulation, social influence, perceived security, and Blockchain functional benefits, to measure trust and satisfaction with relationship quality, which may influence the intention to use Blockchain. A sample of 460 people participated in the online questionnaire survey, which was then evaluated with SmartPLS 3. The findings reveal that the social influence and Blockchain functional benefits have a substantial impact on relationship quality, which further results in a positive impact on Blockchain usage intention as well. This study can serve as a reference for companies that need to consider the factors discussed in this study when implementing Blockchain technology to achieve marketing goals and generate sustainable Blockchain usage intentions.

Purpose: This study aims to enhance the performance of Knowledge management (KM). Additionally, the advantages and the applications of this export system and the smart systems are analyzed. Theoretical framework: Selecting an algorithm isn’t an easy process. With a deep exploration of techniques and algorithms, the appropriate algorithm should be chosen and implemented to ascertain the solution for the problems like analyzing the trend of the business, identifying the age group, and finding the most desired articles and publications. Design/methodology/approach: Contented and Expressive review approaches are implemented to conduct the research. The investigators significantly studied the materials associated with robots and expert systems in the reference to knowledge management in libraries. The results are obtained using the data visualization tool tableau. the Genetic algorithm is also used to analyze the results. Findings: Smart systems are not easy to implement in knowledge management because knowledge management contains a large number of datasets. It has to be categorized first, then needs to be analyzed and the decisions must be taken accordingly.   Research, Practical & Social implications: The expert systems and the robots are to be implemented in the KM so the knowledge management will have enhanced performance with the help of the implementation of smart systems. Originality/value: In the study, the Genetic algorithm is used to find the analysis results. This algorithm was chosen because it works well in a noisy environment and is also easy to understand along with this GA is compared with the neural network algorithm.

The Fourth Industrial Revolution (4IR) has transformed organizations by integrating advanced technologies like artificial intelligence (AI), the internet of things (IoT), and big data analytics into their operations. This study explores how Knowledge Management (KM) and Business Intelligence (BI) contribute to improved business outcomes. BI supports data-driven decision-making, while KM fosters sustainability, collaboration, and innovation, giving businesses a competitive edge. The research examines KM and BI strategies across various industries, including healthcare, business, finance, academia, and government, using a mixed-methods approach with regression analysis, sentiment analysis, and descriptive statistics. A survey of 500 industry professionals revealed that healthcare and industrial sectors were the most motivated to adopt these technologies, while retail and public management were less inclined. Sentiment analysis of discussions highlighted concerns about privacy and job displacement, but also optimism about the potential benefits. Benchmarking pointed to the need for improvements in knowledge sharing, data accuracy, and system integration. Predictions suggest that by 2030, the increased use of KM and BI will enhance operational efficiency, employee engagement, and return on investment (ROI).