This study aims to investigate the impact of Business Intelligence Systems (BIS) on the quality of strategic decision-making in top-level management. The independent variables in this study are Data Quality, Data Visualization, and BI Management, while the dependent variable is the Quality of Strategic Decision-Making. Additionally, the study explores the moderator variable, BI Scope, to further understand the relationship between BIS and the quality of strategic decision-making. By providing valuable insights into the relationship between BIS and the quality of strategic decision-making, this study contributes to the existing body of knowledge on business intelligence and strategic decision-making. The findings show that BI Management, BI Scope, Data Quality, and Data Visualization have substantial and favorable correlations with the quality of strategic decision-making. Effective BI Management techniques contribute to higher decision-making quality, emphasizing the necessity of BI resource management. The study also underlines the importance of BI Scope as a moderator variable, demonstrating its impact on the connection between BI and quality of decision-making. In addition, the research shows that Data Quality and Data Visualization have a considerable influence on strategic decision-making quality. Using effective visualization tools and ensuring high-quality data improves the results of decision-making processes. The interaction impact between BI Scope and Data Quality, on the other hand, was determined to be non-significant.

With the hope of improving students' social interactions who have been diagnosed with Autism Spectrum Disorder (ASD) in Saudi Arabia, the current study set out to examine the effectiveness of peer-mediated therapies delivered through the ubiquitous social media platform Snapchat. Thirty kids with ASD and 15 generally developing peers participated in the study. Alterations in social communication difficulties and observable social interactions were evaluated before and after the intervention to determine its efficacy. The results of the research revealed significant improvements in both self-reported difficulties with social communication and the quality of participants' interpersonal relationships. These findings demonstrate the groundbreaking methodology's deep applicability and widespread cross-cultural significance. Individuals with ASD have shown to benefit greatly from individualized, technology-based therapy to improve their social interactions, as shown by this study.

Lesotho faces fiscal deficits due to high government expenditure as characterized by the huge wage bill regarded as one of the highest in the world (UNICEF, 2018). The aim of this research paper is to investigate the tax revenue impact as a share of Gross Domestic Product (GDP) on economic growth in Lesotho. This research is provoked by the theoretical postulations and empirical evidence that their relationship is positive up to a certain optimal level which is the point at which economic growth rate is maximized. The study used data from 1988 to 2017 to investigate the relationship between tax burden and economic growth in Lesotho by applying the log-linearized model of Scully’s tax optimization model transformed into an ARDL bounds testing framework. Granger causality test and error correction model was employed to investigate the long run relationship between tax burden and economic growth in Lesotho. The findings of study revealed a long-run relationship between economic growth rate and tax burden with a unidirectional causality running from economic growth to tax burden. Granger causality revealed no causal effect running from tax burden to economic growth in Lesotho despite expectation of significant causal effect following both theoretical and empirical literature from various studies. Error correction results further supported a co-integrating relationship running from economic growth to tax burden with 100 percent speed of adjustment in the short-run towards a long-run equilibrium level. An optimal tax burden could not be established as the variables of interest were negative and insignificant signifying the insignificance of tax policy in stimulating the economic performance.

The use of data mining to predict early employment readiness of students is gaining importance due to the expansion of data production in various industries. This study aims to address the employability issue in Middle Eastern nations by utilizing an Adaptive Neuro-Fuzzy Inference System (ANFIS) data mining technology. The experimental investigation used data from tracer studies conducted by three Jordanian universities, consisting of 22 parameters. Results showed that despite achieving an accuracy of 94% for the graduate dataset, ANFIS exhibited high complexity due to the large number of attributes used. The study has implications for selecting relevant variables and investigating multiple aspects. Data mining has various applications, including classification, clustering, regression, association rule development, and outlier analysis. As data production continues to expand, this study provides insights into the potential use of ANFIS in predicting early employment readiness of students in Middle Eastern nations.

The present research examines the debated relationship between quality management and innovation using a multidimensional quality management perspective. The quality performance that is supposed to result from the adoption of quality management is investigated further as a possible mediator between quality management and innovation in the higher education sector. The data needed to test the hypotheses was gathered by sending a survey via the internet to the faculty members at universities in the United Arab Emirates. Applying the approach of structural equation modelling with partial least squares, the hypothesised associations between 175 respondents are evaluated. According to the findings, implementing rigorous quality management has a direct as well as indirect impact on innovation performance via its impact on quality performance. The impacts of soft quality management on hard quality management have indirect consequences on innovation performance. The association between rigorous quality management and innovation performance is moderated in part by quality performance. This study provides one of the initial studies to apply the multidimensional method of quality management in higher education and has the potential to assist directors in better comprehending the interdependencies between soft and hard quality practices.

This study has examined factors, such as technology and employee influence on artificial intelligence (AI) adoption of e-innovative projects in the United Arab Emirates. The present study revealed the success or failure of e-innovation adoption in the public sector of the UAE and hinted at potential e-innovative projects to consider essential factors before adopting it. The study's sample covered the government sector, and the data collection method was a survey questionnaire with a sample size of 1037 responses made up of government employees. This paper was mainly built upon the diffusion of innovation and technology acceptance theories. The analysis findings showed that technology (an external factor) significantly and positively contributed to adopting AI e-innovation technology. Further analysis revealed that employee (internal factor) proxies directly influenced the adoption of AI e-innovation technology. Overall, internal and external factors contributed to adopting e-innovation technology in the United Arab Emirates. For future directions, additional factors related to the market should be considered to explore their contribution.

Digital information has had a significant impact on higher education, transforming the way students learn and interact with course materials, professors, and their peers. Education systems that place a high priority on learning satisfaction and tutor quality frequently ignore the problem of limited access to digital information and technology. In this study, we provide an integrated model that examines how the TAM constructs of digital information in education (DIE) are affected by digital information flow, technological readiness, learning satisfaction, and tutor quality. We provide information on the results of a project evaluation that examined how digital information is used in higher education. We gathered information from a survey of 594 college students to validate our model and hypothesis. Our research suggests that external factors that improve users' technological readiness and learning satisfaction may have an impact on how valuable they perceive DIE to be. A user's traits, particularly their level of technological preparedness, have a significant impact on how simple technology is to use. The user's perceived usefulness of the technology may also be further enhanced in some cultures by the tutor’s perceived excellence. External elements like the flow of information may have a significant impact on the intention to use technology.

This survey aims to provide a coherent and bibliometric overview of the theories and constructs employed in smart homes acceptance and adoption literature. To achieve the study aims, we conducted a systematic search for every article related to the SH concept, services and applications, user acceptance and adoption, and integrated IoT home appliances and devices, in 10 major library databases, namely, IEEE Digital Library, ACM Digital Library, Association for Information Systems (AIS), Elsevier, Emerald, Taylor and Francis, Wiley InterScience, Springer, Inderscience, and Hindawi. These databases contain literature focusing on smart home adoption using IoT technology. 40 research articles of journal and peer-reviewed conferences were found relating to our research objective, presented and distributed chronologically, by publisher, country, theory and model, key construct, and with full bibliometrics for each article. Additionally, this survey includes a word cloud and a taxonomy of the entire factors used to understand users’ acceptance and adoption of smart homes in different contexts and applications. This study has many advantages in covering the current research gap in the literature and also the researchers identify theoretical and practical research implications, research limitations, and recommendations for improving the acceptance and usage of smart homes literature.

The metaverse is an imaginary network of parallel universes. Using this technology might liven up dull lecture halls. By expanding synchronous communication into the "metaverse," many individuals may have meaningful conversations and exchange perspectives. This research focuses on finding out how medical students in the UAE feel about the metaverse system. The conceptual model incorporates elements from the Technology Acceptance Model (TAM), including perceived value and perceived ubiquity as adoption determinants. To test the validity of the suggested framework, a survey was developed and distributed to 369 full-time students at one of the universities in the United Arab Emirates (UAE). Machine learning (ML) and structural equation modeling using partial least squares (PLS-SEM) are used for data analysis. According to the results, the extent to which users saw value in and adoption of the metaverse system was a significant factor in whether or not they intended to participate. This study was helpful since it elucidated the relative significance of various healthcare components, allowing professionals to prioritize their efforts better.

The purpose of this study is to determine the impact of cloud-based solutions on the digital transformation of human resource (HR) practices in Jordan. The study is quantitative in nature and the data was gathered from primary sources by gathering the responses from 346 respondents. The SEM technique was used for the purpose of determining the direct effect. The study found that infrastructure as a service, performance as a service and software as a service had significant and positive impact on the digital transformation of the HR practices. The information gathered from the secondary sources was provided with reference and was also well paraphrased to avoid the issue of similarity. The study focused on the public sector which restricts the results of this study to this sector only. On the other hand, only one country was considered in this study i.e., Jordan. The research is considered as the first attempt to examine the impact of cloud-based solutions on the digital transformation of HR practices in a developing country such as Jordan.