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Students pursuing different professional courses at the higher education level during 2021–2022 saw the first-time occurrence of a pandemic in the form of coronavirus disease 2019 (COVID-19), and their mental health was affected. Many works are available in the literature to assess mental health severity. However, it is necessary to identify the affected students early for effective treatment.

Predictive analytics, a part of machine learning (ML), helps with early identification based on mental health severity levels to aid clinical psychologists. As a case study, engineering and medical course students were comparatively analysed in this work as they have rich course content and a stricter evaluation process than other streams. The methodology includes an online survey that obtains demographic details, academic qualifications, family details, etc. and anxiety and depression questions using the Hospital Anxiety and Depression Scale (HADS). The responses acquired through social media networks are analysed using ML algorithms – support vector machines (SVMs) (robust handling of health information) and J48 decision tree (DT) (interpretability/comprehensibility). Also, random forest is used to identify the predictors for anxiety and depression.

The results show that the support vector classifier produces outperforming results with classification accuracy of 100%, 1.0 precision and 1.0 recall, followed by the J48 DT classifier with 96%. It was found that medical students are affected by anxiety and depression marginally more when compared with engineering students.

The entire work is dependent on the social media-displayed online questionnaire, and the participants were not met in person. This indicates that the response rate could not be evaluated appropriately. Due to the medical restrictions imposed by COVID-19, which remain in effect in 2022, this is the only method found to collect primary data from college students. Additionally, students self-selected themselves to participate in this survey, which raises the possibility of selection bias.

The responses acquired through social media networks are analysed using ML algorithms. This will be a big support for understanding the mental issues of the students due to COVID-19 and can taking appropriate actions to rectify them. This will improve the quality of the learning process in higher education in Oman.

Furthermore, this study aims to provide recommendations for mental health screening as a regular practice in educational institutions to identify undetected students.

Comparing the mental health issues of two professional course students is the novelty of this work. This is needed because both studies require practical learning, long hours of work, etc.

Despite the increasing demand for renewable energy (RE) as a low-carbon energy source, the transition to RE is very slow in many regions, including Oman, the case country for this study. It is critical to offer strategic insights to energy supply chain participants towards the sustainable transition to renewable energy (STRE). The purpose of this study is to identify viable RE sources in Oman as a case study of a GCC member country, develop a comprehensive framework of STRE, and suggest future research opportunities.

The paper addressed this problem through a country/regional study of Oman by conducting a systematic literature review (SLR) of RE-related peer-reviewed publications spanning over 21 years from January 2000 to February 2021. The qualifying articles are evaluated using template analysis qualitatively to identify viable renewable energy sources, build a holistic framework of STRE and recommend future research opportunities.

Findings confirm the potential of solar, wind, biomass and geothermal energies driven by environmental, economic and social sustainability concerns. However, results suggest that to fast-track the STRE, more emphasis should be accorded to solar and wind energies owing to the geographical composition of Oman. Findings reveal that policies and regulations, advanced and cost-effective technologies, subsidy regimes, grid connectivity and capacity, storage capacity and land availability influence the STRE. Gaps in the literature are identified from the results to clarify and suggest future research opportunities.

To the best of the authors’ knowledge, this is the first study that conducted an SLR that was evaluated using the template analysis technique to build a novel and updated framework that facilitates a crystalline understanding of STRE to guide policymakers and professionals in strategic decision-making.

This study aims to examine the association between responsible leadership and work engagement through the mediation of knowledge sharing. Further, the study explored the boundary condition of helping initiative behavior (HIB) between responsible leadership and knowledge-sharing (KS) behavior.

Considering work engagement as a global challenge, the data for this study was collected from 386 employees working in various organizations on convenience basis. Specifically, the data was collected in two waves through a questionnaire-based survey method and structural equation modeling was used for hypotheses testing.

The results reveal that responsible leadership directly and indirectly (through knowledge sharing) affects work engagement. In addition, HIB strengthens the association between responsible leadership and knowledge sharing.

The study collected data from a developing country. However, the findings suggest management should implement such practices that enable leaders to be more responsible. Such leaders create a learning environment that enhances knowledge sharing and promotes work engagement.

Based on social exchange, this study explored the mediating role of KS behavior between responsible leadership and work engagement and the conditional role of HIB between responsible leadership and KS behavior.

This study contributes to the current body of literature on students' understanding of academic misconduct, plagiarism, forms of plagiarism, the reasons they plagiarize, the sanctions imposed by academics for plagiarizing and the methods to address plagiarism in written assessments within the Faculty of Natural Sciences, University of Guyana, which was investigated in 2021.

The research design was descriptive and grounded in the pragmatism paradigm. The methodology employed was quantitative, consisting of the collection of data through an online, self-administered questionnaire-based survey.

The results showed that despite students having a conceptual understanding of academic misconduct and plagiarism, they intentionally and unintentionally plagiarized their written assessments, mainly because of the assessment workload (64.9%), busy schedule (52.8%), not understanding the assessment (46.3%) and not knowing how to correctly cite sources (44.6%). Prevalent forms of plagiarism committed by students included finding synonyms for the author’s language while keeping to the same general structure and meaning of the original work (48%) and neglecting to cite sources, misquote sources or unintentionally paraphrase a source by using similar words, groups of words and/or sentence structure without attribution (42%). Academic sanctions commonly include giving an overall reduced grade, giving a warning and asking the student to redo the plagiarized work. The study showed that students preferred flexible and lenient penalties to address plagiarism and objected to sanctions that may jeopardize their academic progression.

An international literature review will demonstrate extensive research on academic misconduct, particularly plagiarism, emphasizing attitudes and perceptions. Despite Artificial Intelligence (AI) technologies and limited software subscriptions, academic misconduct in Guyana is still poorly understood. Therefore, this study adds to the literature by evaluating tertiary education students' perceptions of plagiarism, given the growing concerns and negative repercussions of plagiarism and student use of AI to produce assignments at this university.

This study aims to investigate the relationship between technology-distinct capabilities (TDC) and innovative work behavior (IWB) through the mediating effect of strategic flexibility (SF), to examine the behavior toward technopreneurship (BTT) among Omani small and medium-sized enterprises (SMEs). Furthermore, technopreneur self-efficacy (TSE) is investigated as a moderating variable between TDC and SF.

Based on the quantitative research design, the survey questionnaire instrument was used to collect data from SMEs’ owners and managers. Using purposive sampling, the study comprised 285 responses from Muscat, Sohar and Al-Buraimi regions. Responses were analyzed through SPSS 25 and Smart PLS 4 using structural equation modeling (SEM).

The main findings revealed a positive and significant influence of TDC and IWB on SF. In addition, SF mediates the relationship between TDC, IWB and TBB. Results showed no effect of TSE on TDC and SF. The study outlines significant theoretical and practical implications. Dynamic capability (DC) theory provided a framework for understanding the highly competitive Omani business climate. The diffusion of innovation (DOI) provides the way forward to SMEs that how they embrace and induce novel concepts, including SF.

The findings of the study can be used by academics and policymakers to develop policies that support SMEs’ technological innovation and adaptability. In the Omani context, policymakers and public managers can utilize this research to evaluate the different technopreneurship support programs and encourage SMEs to adopt digital technology to capitalize on the nation’s entrepreneurial dynamic.

When the repercussions of COVID-19 were being absorbed by the world, the higher educational institutions (HEIs) were conceiving of strategies to run educational institutions on remote basis too, including the challenges linked with the teaching–learning as well as the management and other departmental needs. Leaning itself on the teaching–learning tectonic shifts amid the COVID-19 climes, the study reviews the status of “readiness” of the HEIs in Oman while bearing this in mind that the usage of information and communications technology (ICT) for distance learning and conventional learning has been considered as one of the parameters to judge the “quality” of the HEIs in Oman.

Documentary analysis alongside an in-depth reading of the quality audit reports sourced from the Oman Academic Accreditation Authority, which are publicly accessible are being referred for driving home the arguments in the study.

The study concludes that despite the case being in favor of distance learning from early on, the same doesn’t get reflected in the conclusions derived in the research conducted for assessing the teaching–learning mechanisms during the COVID-19 period. Therefore, the HEIs’ “readiness” in terms of ensuring the smooth transitioning to the remote learning pedagogical arrangements for meeting the challenges of the COVID-19 wasn’t efficacious.

The present study may be followed up with an understanding as to how the HEIs of Oman need to incorporate the perspectives of all the concerned stakeholders for the refurbishment of the teaching–learning process, especially in times of contingencies.

Apart from the policy-makers, the management of the HEIs of Oman needs to appreciate the need to be proactive and appreciative of the inclusion of ICT tools and techniques in the mainstream pedagogical settings.

Notwithstanding the emphasis upon the preparedness and readiness for tackling the challenges posed by the COVID-19 for the HEIs in Oman, no study has attempted to delve into the issue succinctly—the present study fills this gap.

Consumer shopping motivations are evolving in tandem with shifts in products, services and the retail landscape. This paper primarily aims to explore what drives shopping behavior among consumers in Oman. Additionally, the paper aims to profile consumers based on their shopping motivations.

Based upon the review of literature, we developed a list of 63 items of shopping motivations. Exploratory factor analysis later led to a 12-factor solution involving 50 items, which were refined further into an 11-factor solution involving 44 items using CFA. A combination of hierarchical and k-means cluster analysis was performed for profiling consumers.

Five distinct segments of consumers that emerged in the Omani food and grocery retail market were derived as Practical Value Seekers, Discerning Shoppers, Selective Online Shoppers, Social Brand Seekers and Instant Gratifiers. Theoretical and managerial implications were discussed.

In theory, this study examines market heterogeneity by considering customer shopping motivations and applies profiling (clustering) techniques to categorize them into distinct market clusters. In practical terms, it provides valuable insights to food and grocery store managers.

This study is novel and the first of its kind, suggesting a typology of food and grocery shoppers in Oman. Research on consumer shopping motivations has primarily focused on consumers in Western countries, particularly in the United States.

Strategic leveraging of Mobile Commerce (M-commerce) holds immense potential for augmenting firm performance within the realm of Small and Medium Enterprises (SMEs) in Malaysia. This study seeks to unravel the important role played by specific factors, namely, relative advantage, security, complexity, firm performance, organizational competence, M-commerce knowledge, competitive pressure, customer value and information intensity in influencing M-commerce adoption and its subsequent impact on SME performance. Drawing on the Technology-Organization-Environment (TOE) framework, the study posits that technological factors (relative advantage, security and complexity), organizational factors (organizational IT competence and M-commerce knowledge) and environmental factors (competitive pressure, customer value and information intensity) collectively shape M-commerce adoption, thereby influencing SME performance.

The study employs a quantitative approach, engaging SME owners in Malaysia as participants, with a sample size of 150 selected through an online survey. Analysis was conducted using Smart PLS, revealing crucial insights.

The investigation revealed a positive relationship between relative advantage, security, complexity, competitive pressure, customer value and information intensity, and the adoption of M-commerce within SMEs in Malaysia. Moreover, a positive relationship was identified between M-commerce adoption and firm performance among Malaysian SMEs. Intriguingly, there was no discernible relationship between Organizational IT competence, M-commerce knowledge and the adoption of M-commerce.

This research contributes to the scant literature exploring SMEs’ inclination toward M-commerce for performance enhancement. The proactive adoption of M-commerce stands poised to empower SMEs in Malaysia, enabling them to play a more substantial role in the national economic structure. Consequently, it emphasizes the need for effective communication of government policies pertaining to M-commerce adoption, particularly among SME stakeholders.

Previous research has found that family characteristics, including family income, entrepreneurship/business experience and family size, can influence offspring’s entrepreneurial potential and perception of the barriers to entrepreneurship. This paper aims to extend this proposition to women in Oman to determine whether family income, entrepreneurship/business experience and family size influence women’s perception of barriers to entrepreneurship

This study is based on primary data that was collected through a structured questionnaire from 123 female respondents at an Omani private university. The data was analysed using PCA, correlation and regression analysis to determine the influence of the family characteristic on the perception of barriers to entrepreneurship.

The findings concluded that the three family characteristics being tested were not able to predict a change in the perception of barriers to entrepreneurship. This contradicts previous research conducted in Western contexts and highlights the potential weakness in family support for female entrepreneurship in Oman.

These results challenge some of the extant findings in the literature, thus enriching the current perspectives on female entrepreneurship and the impact of Omani family characteristics, in terms of income, economic background and family size, on the perception of barriers that hinder entrepreneurship among female students

The Metaverse is an immersive virtual world where individuals interact with each other using an avatar. The Metaverse is promised to offer several potentials for different sectors. While the Metaverse promotes innovative interaction between individuals (e.g. learners), there is a scarcity of knowledge on what influences its acceptance and use in higher educational institutions (HEIs), particularly in developing countries. Thus, this paper aims to identify the factors that affect the users' intentions toward Metaverse technology for educational purposes in the HEIs in Jordan.

A study model was created by incorporating variables from the unified theory of acceptance and use of technology (UTAUT) (performance expectancy, PE; effort expectancy, EE; social influence, SI; and facilitating conditions, FC) and information system success (ISS) model (user satisfaction, SAT; system quality, SQ; service quality, SVQ and information quality, IQ) with perceived curiosity (PC) and hedonic gratification (HG) constructs. Both PC and HG were added as context-related factors that could contribute to improving the applicability of UTAUT and ISS to a wide range of technology use contexts. Data were gathered from 441 Jordanian university students using an online questionnaire.

The analysis of the structural model revealed that users' behavioural intentions toward using Metaverse were significantly affected by user satisfaction (SAT), performance expectancy (PE), facilitating conditions (FC) and hedonic gratification (HG). Also, information quality (IQ) and services quality (SVQ) were revealed to have a significant influence on user satisfaction. Likewise, the results illustrated a significant impact of systems quality (SQ), information quality (IQ) and service quality (SVQ) on PE. Lastly, a significant effect of PC on the EE factor was found.

This study will shed light on a number of practical implications for developers, designers, service providers and decision-makers supporting the acceptance and adoption of the Metaverse technology in the educational context. Also, it will contribute to developing the right strategies, and Metaverse content which will draw the attention of learners.

As per the surveyed literature and the researcher's prior knowledge, this is one of the first studies that integrate the UTAUT model, ISS model and two contextual factors (PC and HG) besides testing the proposed model in a developing country (Jordan). This paper is one of the few in which the individuals' acceptance behaviour of Metaverse technology was examined in the HEIs context.