Using adaptive learning technologies, personalized feedback, and interactive AI tools, this study investigates how these tools affect student engagement and what the mediating role of individuals’ digital literacy is at the same time. The study will target 500 students from different faculties such as science, engineering, humanities, and social sciences. With the changing trends in educational technology, it is important to know if these tools allow students to interact with learning materials. Through this study, we explore how adaptive learning technologies, which adapt content to students’ progress, are influenced by student motivation and participation during the learning process using AI tools that provide real-time feedback and interaction. Also, digital literacy is presented as a moderating factor that may either accelerate or impede the effectiveness of these tools. These findings demonstrate that more adaptive learning technologies, which have organized feedback, and interactive AI tools help improve student engagement. Additionally, students with higher levels of digital literacy are more involved with digital tools. This research recognizes that teachers should incorporate these technologies into their courses in such a manner as it synergizes with student’s digital capabilities to reap the benefits of technology on students’ engagement and learning outcomes.

This study aims to investigate the main technological and socio-environmental factors influencing the adoption intentions with regard to AI-based technologies at the organizational level. A conceptual model based on innovation diffusion theory (DOI) and the technology-organization-environment (TOE) framework is proposed and tested empirically using survey-based data collected from 512 senior IT/IS managers in public/private organizations located in Jordan. The results indicate that relative advantage, top management support, cost-effectiveness, competitive pressure, vendor support, compatibility, AI strategic alignment and availability of resources, positively influence the intention to adopt AI-based technologies. The analysis demonstrated that the influence of market uncertainty on adoption intentions is insignificant. It was found that government regulation and complexity negatively influence adoption intentions. The findings of the study would be valuable for AI-based technology providers, IT managers and top management in organizations, and government bodies, in terms of building effective policies to promote the successful adoption of AI-based technologies.

Despite the fact that online purchase intention has been widely investigated, little is known about the e-retailer-based signals used to reduce online customers’ uncertainty perception in high-uncertainty-avoidance (UA) societies. Thus, based on signaling and uncertainty literature, this study investigates return policy leniency (RPL), cash on delivery (COD), and social commerce constructs (SCCs) as the costly signals e-retailers use to increase perceived trust and reduce perceived purchase uncertainty among customers in high-UA societies. An analysis of empirical data from 560 e-commerce users from Jordan reveals that RPL, COD, and SCCs are key enablers of customer trust. Furthermore, customer trust is positively associated with customer purchase intention. The implications for both theory and practice are highlighted.

Various scholars have empirically investigated customer beliefs regarding satisfaction, loyalty and trust in the context of B2C e-commerce in several countries. However, the number of investigations into such important aspects of e-commerce in developing Arab countries, such as Jordan, is limited. Therefore, the main aim of this study is to explore the main factors that affect the degree to which consumers in Jordan are satisfied with, loyal to and trust B2C e-commerce. This research relies on previous and related literature to formulate a conceptual research model that proposes relationships between online trust, satisfaction and loyalty, and their determinants. To examine the proposed model, a self-administered paper-based survey questionnaire was issued to B2C e-commerce customers in a Jordanian private university. The findings suggest that customer loyalty to B2C e-commerce in Jordan is significantly influenced by online customer satisfaction, electronic word of mouth (eWOM) and online trust.

Cloud computing technology has proved to be an important technological solution, especially for small and medium- sized businesses (SMEs), by providing many opportunities for companies to enhance their operations, reduce cost, improve scalability and flexibility, and make more efficient use of technology. Despite its benefits, most SMEs are still hesitant about adopting cloud computing. The purpose of this study is to assess the factors that influence cloud computing adoption among SMEs in Jordan. This study does so by developing a research model based on the Technology Organization Environment (TOE) and Diffusion of Innovation (DOI) .These theories overlap in terms of the characteristics that strengthen the explanation of adoption. An online questionnaire was used to collect data from 244 SMEs registered in Jordan. A multiple regression test was implemented to examine the proposed model. The results indicate that seven factors significantly affect cloud computing adoption among SMEs. Among these factors, cost reduction was found to be the strongest predictor, while the weakest predictor was firm size. However, the firm’s scope insignificantly influenced cloud computing adoption among SMEs in Jordan. This finding could provide insights for SMEs decision- makers when it comes to adopting cloud computing. In addition, it provides insights for practitioners in terms of recognizing the important factors that encourage or prevent SMEs from adopting cloud computing.