This quantitative study examined the relationships between privacy, trust and level of service quality, and customer satisfaction. Jordanian firm employees involved in CRM technology were the study samples. Data from 620 completed questionnaires were analyzed utilizing AMOS software version 23. The study hypotheses were tested through Structural Equation Modelling (SEM). The causal relationships among the study’s main variables were examined as well. Results showed a positive impact of trust, privacy, and level of service quality on customer satisfaction. Managers and practitioners could pursue this study results in their CRM systems implementation. Additionally, the relations between privacy, trust and level of service quality, and customer satisfaction could be examined further as these relations in CRM systems have not been adequately examined, especially in emergent industries of developing countries.

Student learning and how their lessons are delivered have been dramatically changed by COVID-19 pandemic, as evidenced by the widespread utilization of e-learning systems when the pandemic hit. However, the use of e-learning among students worldwide has not been as effective. The e-learning systems success model after the pandemic should be revised. This study examined the role of monitoring quality to validate the e-learning systems success using previous e-learning and information systems success models. Structural equation model was used in data analysis, involving data obtained from 800 students. Results demonstrated positive impacts of information quality, system quality and service quality, on user satisfaction, and positive impact of system use of user on student satisfaction and consequently on student loyalty. Monitoring quality did not show a positive impact on user satisfaction. Significant impact of user satisfaction on learning effectiveness was also shown. This study showed some significant implications for e-learning systems success models both in theory and in practice.

The current study aims to assess the factors that could affect students’ use of ChatGPT. The study proposed a theoretical model that included six factors. Data was collected from 518 students using a questionnaire. The data were analyzed using Structural Equation Modeling to identify the relationships and test the hypothesis. The findings revealed that performance expectancy and social trust significantly influenced students’ intentions to use ChatGPT. Contrary to expectations, both social influence and effort expectancy had insignificant effects. By elucidating the core factors affecting the utilization of ChatGPT, trust had a significant impact on the intention to use ChatGPT. Furthermore, trust mediates the relationship between perceived security and intention to use ChatGPT, this study can provide valuable insights for policymakers. Moreover, this study contributes to the existing literature by setting the foundation for future research seeking a deeper understanding of the factors influencing the use of other AI technologies in teaching and learning in Electronic Public Facilities.