COVID-19 pandemic has resulted in the closure of higher education institutions (HEIs) worldwide, including in Oman. In response, HEIs in Oman quickly transitioned from traditional classrooms to online e-learning methods. This sudden shift has had a significant impact on students' learning behaviour, particularly among private HEI's students who have fewer resources and support compared to their counterparts in public HEIs. This chapter examines the impact of COVID-19 on public and private HEI's students' behavioural intentions (BIs) towards e-learning. It uses the Technology Acceptance Model to analyse the relationships between perceived usefulness (PU), self-efficacy, perceived ease of use, environment readiness, and BI. Data was collected through an online survey in Oman and analysed using IBM SPSS AMOS. The chapter highlights the significant impact ofPU, efficiency, cost-effectiveness, and self-efficacy on students' BI to use e-learning. It also emphasises the importance of user-friendly platforms and understanding students' expectations in shaping their e-learning experience. These insights contribute to the knowledge base on e-learning and have implications for educational institutions in the GCC region, informing further research and policy development. The study provides valuable insights for institutions adapting and enhancing their online learning strategies in response to the COVID-19 pandemic.

Job-related stress and its influence on work-life have emerged as a challenging task at all levels of management. With the emergence of COVID-19, stress has become one of the major problems for the workforce. The main purpose of this chapter is to determine the impact of job-related stress experienced by higher education institutions (HEIs) employees on their professional and personal life during the period of the coronavirus pandemic. For this purpose, several variables are examined during the COVID-19 pandemic, such as Demographics, Health Conditions, Workplace Stress, and Work-Life Balance (WLB). After descriptive statistics and bivariate correlations between the study variables were presented, the analysis of variance and structural equation modelling analysis resulted in the test of the hypotheses under study. The study's findings demonstrate the amount of job-related stress experienced by HEIs employees and its impact on their professional and personal lives during the pandemic, based on their self-evaluation. Results from sample data reveal that only the health condition of the respondents significantly controls the level of stress and WLB, irrespective of their demographic profile. The HEIs employees are experiencing both negative and positive stress, which are mutually independent.

The twenty-first century has witnessed a wide variety of digitally connected platforms for mutual communication, collaboration, and creative expression. The digitally connected devices increase the exposure to untrusted users. This chapter describes several types of social media and throws light on the latest trend of digitally stored Big Social Data (BSD). Platforms like Instagram, Snapchat, Pinterest, and Imgur are some of the social media in this category. Social Blogging sites like Word Press, Medium, and Tumblr have engaged users by their written content. The main purpose of a blogging site is not to create social networks, but the dissemination of information. Social media is regulated by trends and popularity. Over the years, apart from pop up ads, several sites and mobile applications solely related to gaming and gambling have been developed.

PurposeThe present paper is an attempt to study Education 4.0 supported by Industry 4.0 tools and techniques. The main purpose of the study is to examine the acceptance and use of one of the internet of things (IoT)-based learning management systems, i.e. videoconferencing application (Google Meet, Microsoft Teams, Zoom, GoToMeeting, WebEx), by academicians of higher education using the unified theory of acceptance and use of technology (UTAUT) model.Design/methodology/approachThe study comprises 218 responses of academicians associated with higher education in the Sultanate of Oman. Descriptive and factor analysis of the collected data are employed using SPSS-26. Further, using Amos-21, the fit and validity indices of the measurement model are computed. Various relationships of the UTAUT structural model along with moderation effects of gender and nationality are tested.FindingsThe results suggest that performance expectancy, effort expectancy and social influence significantly predict behavioral intention. In turn, behavioral intention and facilitating conditions also significantly predict the use behavior of academicians for videoconferencing in higher education. Finally, gender moderates two out of four UTAUT relations, but nationality does not moderate any of these relations.Originality/valueA lot of prior studies investigate several models to use technology-enabled pedagogy from educators' or students' perspectives. There are very limited studies that examine IoT-based learning tools within the UTAUT environment. Additionally, no study is available that considers UTAUT relations for the use of videoconferencing in higher education. Also, in the present study, one more moderator, i.e. nationality, is tested.

A smart city is defined as a one that provides solutions to rapid urbanization, exploding population, scarce resources, congested traffic, and energy management through the effective and integrated use of information and communication technology. The conceptualization, integration, and implementation of smart cities have been recognized and seen as a means to optimize the limited resources and improve the quality of human lives. The smart cities planning, designing, and development have been affected due to big data storage, big data governance, Internet of Things (IoT), and artificial intelligence (AI) techniques. The smart cities' solutions cover different themes of varying importance such as smart health, smart education, intelligent transportation, smart energy, smart governance, etc. The emerging technologies are the one which are presently under development or might be developed in the future, and which can have a wide impact on research, business, and social lives. The emerging technologies are the groups of technologies that have been partially explored, continuously evolving, and under development such as, IoT, big data, machine learning (ML), social network, and cloud computing. The emerging technologies have created renewed interest in smart cities' solutions. The smart cities' progress and advancement are the results of the successful exploitation of emerging technologies. This paper aims to investigate and discuss the success stories of emerging technologies in smart cities' solutions. The emerging technologies included in the study are the IoT, big data, and AI. The paper further summarizes a process of applying tools and techniques for the successful initiative of transforming a traditional city into a smart one using emerging technologies.

Purpose The purpose of this paper is to investigate students’ attitude based on affective, behavioural and cognitive components. It will ascertain whether there is a link between the three components of attitude, which leads the possible classification of the elective courses. Design/methodology/approach The current study considers the students of the International Business Administration Department from Rustaq College of Applied Sciences, Ministry of Higher Education, Sultanate of Oman, during the academic year 2016–2017. The list of the elective courses was obtained from the existing study plan. A total of 101 students assessed elective courses’ affective and cognitive learning with the use of a web-based survey instrument. Findings An empirical analysis of the selection criterion was performed employing fuzzy set qualitative comparative analysis. The results of this study found that students rated 17 elective courses into 8 different configurations (triodes) based on various degrees assigned to attitudinal variables. Research limitations/implications The present study explores the interaction between affective and cognitive factors in determining the selection behaviour of students. It is an investigation into the context of student choices regarding elective courses, especially the decision to select or not to select available courses. Originality/value The world of feelings and beliefs is always open to learning and self-development for the students. Students are continuously involved in taking charge of high-stakes decisions; one of them is the selection of elective courses. However, the critical components into the overall evaluations of their selection behaviour, such as feelings and beliefs, are not well studied.