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In any developing country, the critical benefits for ensuring proper utilization of e-government learning services have basically emerged from the integration of underlying processes – not only across different levels of government but also across different functions and agencies. The literature showed a notable lack of research to underline the limited use of e-government learning services in a university setting. Therefore, this study was conducted to examine students' intention to adopt e-government learning services in a developing country. Precisely, the existent to which reputation, social influence, information quality and system quality of e-government learning services would influence students' trust, perceived usefulness and perceived learning values was investigated.

The effect from these variables on students' intention to use e-government learning services was also investigated. A total of 406 questionnaires were collected and analyzed using partial least squares (PLS) modeling.

The results showed varying relationships between the study's variables. It is anticipated that understanding these relationships can predict future learning trends of e-government learning services use among university students, thus helping decision makers plan ahead, prioritize tasks and make better decisions.

Knowledge about students' intention to use e-government learning services is even useful for the implementation of other services by higher education institutions. This study also offers some implications for practitioners and researchers concerned about the application of e-government in students' learning development.

This study explored the themes and sentiments of online learners regarding the use of Generative Artificial Intelligence (AI) or “generative AI” technology in higher education.

English-language tweets were subjected to topic modelling and sentiment analysis. Three prevalent themes were identified and discussed: curriculum development opportunities, lifelong learning prospects and challenges associated with generative AI use.

The results also indicated a range of topics and emotions towards generative AI in education, which were predominantly positive but also varied across male and female users.

The findings provide insights for educators, policymakers and researchers on the opportunities and challenges associated with the integration of generative AI in educational settings. This includes the importance of identifying AI-supported learning and teaching practices that align with gender-specific preferences to offer a more inclusive and tailored approach to learning.

This study proposes a research model to identify the relevant constructs of employee resistance and symbolic adoption in pre-implementation stage of enterprise resource planning systems in manufacturing industries, drawing suitable support from the existing body of literature. The proposed model is a combination of the status quo bias theory and absorptive capacity theory to measure employee resistance that negatively lead to symbolic adoption of a user.

This research used a self-administered questionnaire to survey 221 participants from five organizations in the manufacturing industry, all working towards deploying enterprise resource planning (ERP) systems.

The results show that factors contributing to status quo bias and absorptive capacity impact end-user grumbling. Furthermore, end-user grumbling affects symbolic adoption substantially.

This study provides researchers, practitioners and ERP vendors a broader overview of employees' resistance and motivation for using newly deployed systems.

In the past two decades, both practitioners and academicians are investigating the technical and non-technical features that assist end-users to adopt the system. Information system theories center on the post-deployment stage, with rare attempts to identify users' resistance and mental willingness to accept technology in the pre-adoption phase, which is very crucial for the success of ERP.

Designers of mobile applications have long understood the importance of users’ preferences in making the user experience easier, convenient and therefore valuable. The cultural aspects of groups of users are among the key features of users’ design preferences, because each group’s preferences depend on various features that are culturally compatible. The process of integrating culture into the design of a system has always been an important ingredient for effective and interactive human computer interface. This study aims to investigate the design of a mobile health (mHealth) application user interface (UI) based on Arabic culture. It was argued that integrating certain cultural values of specific groups of users into the design of UI would increase their acceptance of the technology.

A total of 135 users responded to an online survey about their acceptance of a culturally designed mHealth.

The findings showed that culturally based language, colours, layout and images had a significant relationship with users’ behavioural intention to use the culturally based mHealth UI.

First, the sample and the data collected of this study were restricted to Arab users and Arab culture; therefore, the results cannot be generalized to other cultures and users. Second, the adapted unified theory of acceptance and use of technology model was used in this study instead of the new version, which may expose new perceptions. Third, the cultural aspects of UI design in this study were limited to the images, colours, language and layout.

It encourages UI designers to implement the relevant cultural aspects while developing mobile applications.

Embedding Arab cultural aspects in designing UI for mobile applications to satisfy Arab users and enhance their acceptance toward using mobile applications, which will reflect positively on their lives.

Most new media research focuses on behavior as a measure of engagement, while the psychological state of being occupied with its content has received little attention. This study examined news engagement beyond pure action observation by exploring young people’s psychological experiences with the news.

The study carried out a digital native’s survey on 212 people (18–28 years). The focus of the survey was on understanding individuals’ engagement with online news using affective and cognitive components. The authors compared the influence of each type of engagement on youth consumption of and attitudes toward online news.

The results of the hierarchical regression analysis showed that affective engagement can be a stronger predictor of online news consumption than cognitive engagement. While affective engagement significantly predicts positive attitudes toward online news, cognitive engagement had no significant effect.

These findings suggest that “engaging the heart” is more influential than “engaging the mind” in drawing young people to the news in today’s information environment. The study thus contributes to the understanding of the cognitive and emotional focus on news content and their importance in shaping young people’s expectations of online news. The findings from this study could have broader implications for future trends in online news consumption.

Governments of the developing countries must be ready to embrace the evolution of information technology. However, the growth in demand for online services and expectations for convenient access to government resources are placing governments under pressure to deliver outstanding e-services. Despite the successful attempts of the Saudi Government to deliver e-government services, the literature still needs to be advanced with evidence to demonstrate the current status of government websites. Additionally, the growth of e-government services should be periodically monitored and evaluated.

This study aims to revisit e-government websites previously surveyed (2006-2012) in Saudi Arabia and examine growth based on the five-stage maturity model. This study supports the approach with a review of the United Nations data and links this assessment with the five-stage maturity model.

The results revealed remarkable improvements in the maturity level of online services provided by the government websites of Saudi Arabia.

The relationship between e-government use and investment decisions appears to be bidirectional, as greater levels of investment seem to offer more opportunities for service improvement.

The outcomes are expected to assist executive authorities in understanding the current situation of e-government and plan appropriate strategic suggestions and development.

The purpose of this paper is to assess the impacts on production of five fruit crops from 1961 to 2018 of energy use, CO₂ emissions, farming areas and the labor force in China.

This analysis applied the autoregressive distributed lag-bound testing (ARDL) approach, Granger causality method and Johansen co-integration test to predict long-term co-integration and relation between variables. Four machine learning methods are used for prediction of the accuracy of climate effect on fruit production.

The Johansen test findings have shown that the fruit crop growth, energy use, CO₂ emissions, harvested land and labor force have a long-term co-integration relation. The outcome of the long-term use of CO₂ emission and rural population has a negative influence on fruit crops. The energy consumption, harvested area, total fruit yield and agriculture labor force have a positive influence on six fruit crops. The long-run relationships reveal that a 1% increase in rural population and CO₂ will decrease fruit crop production by −0.59 and −1.97. The energy consumption, fruit harvested area, total fruit yield and agriculture labor force will increase fruit crop production by 0.17%, 1.52%, 1.80% and 4.33%, respectively. Furthermore, uni-directional causality is correlated with the growth of fruit crops and energy consumption. Also, the results indicate that the bi-directional causality impact varies from CO₂ emissions to agricultural areas to fruit crops.

This study also fills the literature gap in implementing ARDL for agricultural fruits of China, used machine learning methods to examine the impact of climate change and to explore this important issue.

Social media addiction has been an ongoing topic of debate for platform developers, well-being and mental health experts. There is a limited understanding of the factors leading to the addiction of young social media users, the consequences of experiencing addiction, and the measures/mechanisms used by parents and platform providers to limit/prevent problematic social media use amongst young users. This systematic review aims to provide a comprehensive overview of the literature concerning these issues.

The Preferred Reporting Items for Systematic Reviews (PRISMA) protocol was used to evaluate and present the results. A total of 45 studies were screened and independently reviewed against predetermined criteria for eligibility.

The results revealed four categories of young users' addiction to social media networks (social, technological, behavioural and mental). Several prevention approaches directed at parents and platform providers were discussed.

This study offers important insights for health policy makers, platform providers, parents and researchers on designing interventions addressing social media addiction amongst young users. It also provides an in-depth understanding of the conceptualization of social media addiction and suggestions on possible actions to prevent it.

The efficiency of fractional derivative and hereditary combined approach in modeling viscoelastic behavior of soft foams was successfully addressed in Elfarhani et al. (2016a). Since predictions obtained on flexible polyurethane foam (FPF) type A (density 28 kg m⁻³) were found very promoting, the purpose of this paper is to apply the approach basing on two other types of foams. Both soft polyurethane foams type B of density 42 kg m⁻³ and type C of density 50 kg m⁻³ were subjected to multi-cycles compressive tests.

The total foam response is assumed to be the sum of a non-linear elastic component and viscoelastic component. The elastic force is modeled by a seven-order polynomial function of displacement. The hereditary approach was applied during the loading half-cycles to simulate the short memory effects while the fractional derivative approach was applied during unloading cycles to simulate the long memory effects. An identification methodology based on the separation of the measurements of each component force was developed to avoid parameter admixture problems.

The proposed model reveals good reliability in predicting the responses of the two considered flexible foams. Predictions as measurements establish that residual responses were negligible compared to elastic and viscoelastic damping responses.

The development of a new combined model reveals good reliability in predicting the responses of the two polyurethane foams type A and B.

The purpose of this study is to investigate the effect of politically connected directors (PCDs), media coverage and their interaction on firm performance in an emerging market economy (UAE).

This study relies on the agency theory and the resource dependency theory and uses a panel data set of a sample of non-financial firms listed in the UAE stock market from 2009 to 2016. Data were analyzed using fixed-effects regression. Instrumental variable regression was used to address potential endogeneity.

PCDs and media are positively associated with firm performance (ROE and Tobin’s q). Media moderates the PCDs–performance relationship, as the interaction between PCDs and media coverage is negatively associated with firm performance. Under growing media attention, reputational concerns prevent PCDs from using their connections to gain particular advantages to their firms to avoid damaging their image.

Regulators need to acknowledge and define the roles of PCDs and media in business governance.

To the best of authors’ knowledge, this study is the first empirical examination testing the effect of the interplay between PCDs and media on firm performance in an emerging market economy such as UAE.