Today, online consumers’ shopping experiences are wholly transformed because of technology to maximize consumer shopping experiences. However, even after increased online shopping after the Covid-19 outbreak, no study has examined the role of demographics in online shopping acceptance. Thus, we filled this gap by employing a cross-sectional design in the UAE and conducting Structural Equation Modelling (SEM). For data gathering purposes, we used structured questionnaires and randomly selected a sample of n = 320 respondents from Al Ain city. Findings revealed strong relationships between Online Shopping, Social Media Usage, and Electronic Word of Mouth (p > 0.000, p > 0.000). Despite the relationships between Social Media Usage, Electronic Word of Mouth, and online shopping acceptance remaining insignificant (p < .384, p < .425), the relationship between Social Media Usage, Online Shopping Acceptance (p > .004) remained significant. Finally, we conducted the mediating analyses and found a substantial mediation of gender between Social Media Usage, Online Shopping Acceptance (p > .000), and Electronic Word of Mouth and Online Shopping Acceptance (p >. 001). Hence, we conclude that people from Al-Ain city primarily rely on online shopping. For this purpose, they consider different factors, including their demographics, i.e., gender, as highly influential on their online shopping acceptance. However, the major limitations of the current study involve selecting gender as the only mediating variable, rejection o two prominent hypotheses, and geographical generalizability of results. Finally, we recommend that future researchers examine the impact of other demographical variables, i.e., age, income, qualification, residence, and others, to examine their impacts on consumer online shopping acceptance.

Literature abounds with research on the benefits of technology and its effect on students’ performance and satisfaction. The use of Learning Management Systems (LMS) such as blackboard, eCollege, Moodle and others are being used throughout the educational sector. Some even incorporate such technology to measure teaching effectiveness and student performance. Furthermore, social websites, like Facebook.com, have become so popular that 85 to 99% of college students use it in one form or another (Hargittai, 2007; Jones & Fox, 2009; Matney & Borland, 2009). This research explores the students’ perspective on how the effectiveness of tools such as Moodle and Facebook.com as well as paper based learning (traditional learning) on their performance. The paper also looks at different factors, such as gender, major type and age to try to shed light on the preferred tool among students to use for education. When it comes to students’ tool preference based on age and gender, we found no significant difference but when looking at students’ majors and time spent in university, we found that Moodle was rated the top, followed by paper-based learning, then Facebook. When viewing students’ perception on effect of these tools on performance, we found no statistical significant difference by age or time spent in the university but did find a significant difference among different genders; where male students showed greater satisfaction than did female students, and statistical significant different among majors.

This research focused on the students' perceptions of the role of Artificial Intelligence in the educational content recommendation system by using the SEM- Artificial Neural Network approach. Data obtained from structured surveys indicated that Artificial Intelligence plays a significant role in the educational content recommendation process. Most relationships proposed in the conceptual model remained significant, with p values as strong as p> 0.000. Further, the IPMA and ANN also revealed in-depth results. Thus, this research concludes that the video recommendation system is helping young students to search for and find the educational content they want. Besides, this system also provides them with a searching facility with fewer efforts, adding more value to YouTube as one of the most prominent digital platforms today.

When linked, Innovation, Entrepreneurship and Leadership provide a platform for Organizational survival. This paper develops a framework for innovation – a necessary condition that requires the appropriate leadership in order to guide its course in the right direction. Innovation Proficiency stems from two major elements: the interior and the exterior. The interior element includes three constituents: knowledge, attitude, and imagination. The exterior element also includes three constituents: culture, resources and habitat. While the exterior element is related to the outer world and one's environment, the interior one relates to us as people. The aim of this paper is to combine and investigate Seelig's model for the Innovation Engine and to evaluate the Kuratko entrepreneurship platform. The paper, which is based on both platforms, evaluates the innovation progression and entrepreneurship base within several industries in the Middle East and North Africa regions (referred to as the MENA region). A survey, which was distributed to leaders in several major industries, was collected, analyzed, and presented.

Smartphone usage is increasing due to several features and opportunities offered by manufacturers and service providers. Existing literature attributes this increased usage to the availability of virtual assistants, mainly voice assistants, that ensure users' facility and maximum benefit. This research also focused on the factors behind voice assistant usage, particularly in iPhones among users in the United Arab Emirates. Notably, the conceptual framework in this research is supported by the Theory of Reasoned Action. The researchers adopted a cross-sectional design and gathered data from n= 251 respondents. Data analysis through Structural Equation Modelling revealed that, Perceived Ease of Use, Subjective Norms, and Perceived Behavioral Control work as significant factors contributing to iPhone-based voice assistant usage. On the other hand, Expectation Confirmation also works as a significant factor in Siri usage. On the other hand, Satisfaction significantly mediated (p> .022) the users’ Expectation Confirmation leading to Siri usage among the respondents. Further, the Artificial Neural Network Analysis (ANN) revealed an overall accuracy regarding Training at 14.8% and 30.8% concerning Testing. Thus, it is concluded that the devices accompanied by ease of use are preferred due to their distinguished services. In this regard, highlighting voice assistants' help also reflects the importance of technology in our daily lives. Especially mobile computing is playing a significant role in improving our everyday technology experiences.