The study aims at exploring the effect of artificial intelligence as measured by machine learning capability and expert systems capability on patient satisfaction. As informant participants, medical staff workers in healthcare institutions in KSA comprise the population of the study. Hence, a sample consisting of 300 participants was used to gather research data via a questionnaire developed based on previous works. By means of Smart PLS 3.0 software, the results indicate that both machine learning and expert systems have significant effects on patient satisfaction. The study concluded that artificial intelligence capability is a cornerstone of patient satisfaction. such a statement encompasses theoretical and empirical implications as stated at the end of this study.

This qualitative study examined the impact of social media characteristics on the attitude of users toward the use of e-services by the Department of Lands and Survey. The study population comprised users of Department of Lands and Survey e-service, while the study sample comprised 407 users. Data from respondents were analyzed using SEM run using Amos (23). Results showed reliability, security, website design, ease of use, awareness, and digital divide as direct significant antecedents of user attitude toward the use of e-services from the Department of Lands and Survey. Also, all antecedents showed direct significant relationships with user attitude. Results showed a direct significant relationship between user attitude and the use of e-services from the Department of Lands and Survey. Through mediation of user attitude, five indirect significant relationships between the antecedents and the use of e-services from the Department of Lands and Survey were found. The inclusion of new antecedents such as privacy and site content may enhance the understanding of how users use e-services provided by the Department of Lands and Survey.

The world of the Internet of Things (IoT), even though it is continuously morphing as a fresh paradigm at the intersection of technology and education, is still struggling with several difficulties that prevent its absorption into the e-learning platforms of higher education institutions (HEIs). The breadth of Internet of Things implementation in developing countries, particularly Jordan, Malaysia, Iran, Saudi Arabia, Iraq, and Bangladesh, remains behind, even though industrialized nations have made significant advancements in their utilization of IoT, with the United Kingdom, the United States of America, China, and Japan acting as prominent examples. In the realm of research that focuses on the progression of the IOT integration into the e-learning systems of economically challenged countries, there is a substantial disparity. In particular, the focus of this research is on Jordan to shed light on the primary variables that are either facilitating or hindering the adoption of the IoT within the e-learning sector of Jordan's HEIs. A comprehensive analysis of previous research has been undertaken as a first stage in this investigation. The goal of this analysis is to identify important factors that are involved in the process of IOT adoption. Following that, we used an inferential technique, collecting data from 306 respondents who were enrolled in Jordanian higher education institutions. During our investigation, we discovered that the rate of the IOT integration was significantly influenced by factors such as accessibility, usability, technical assistance, and individual capabilities. In addition, our findings suggest that factors such as attitude, behavior, financial preparedness, dependability, and training have a substantial impact on the adoption of the IOT. On the other hand, the study seemed to indicate that characteristics such as class capacity, awareness, system resources, and course design had a minor influence on the adoption rates inside HEIs. In conclusion, this study provides tangible suggestions to strengthen the integration of the IoT inside Jordanian HEIs. These recommendations provide significant insights that can be used by policy architects, government entities, and higher education institutions to overcome the challenges that relate to the deployment of IoT in the higher learning sector.

This study employed quantitative methods to evaluate the influence of adaptive learning technology on the cognitive flexibility of students with special needs. Participants were recruited from special education schools using a purposive selection strategy. The Wisconsin Card Sorting Test (WCST) was utilized as a tool to assess cognitive flexibility. The data was analyzed using descriptive statistics, paired-samples t-test, correlation analysis, and regression analyses. The findings demonstrated a notable enhancement in WCST scores after the intervention, suggesting that adaptive learning technologies have a beneficial effect on cognitive flexibility. Regression studies revealed that various types of adaptive learning technologies had varied levels of efficacy, with Tech A showing the most significant beneficial impact. Surprisingly, demographic factors such as age, gender, and educational attainment demonstrated little and statistically insignificant associations with alterations in cognitive flexibility levels. The findings emphasize the potential of adaptive learning technologies as effective therapies for improving cognitive flexibility in kids with special needs. It underscores the significance of evaluating specific characteristics and design principles to maximize their efficacy.

The study investigates the impact of product quality and social media marketing on brand loyalty through customer satisfaction in the context of Japanese restaurants in Jakarta. Utilizing primary data from 203 respondents who frequented these restaurants, collected via questionnaires employing purposive sampling, the research employs partial least squares (PLS) analysis through SmartPLS 3.3.3 software. Results indicate direct positive relationships among variables. However, no direct positive relationship was found between product quality or social media marketing and brand loyalty. Instead, both product quality and social media marketing indirectly influence brand loyalty through customer satisfaction. The study highlights direct positive associations between product quality and customer satisfaction, social media marketing and customer satisfaction, and customer satisfaction and brand loyalty. Nevertheless, no direct positive link was found between product quality or social media marketing and brand loyalty. The indirect effects reveal that product quality affects brand loyalty through customer satisfaction and social media marketing influences brand loyalty through customer satisfaction as well. These findings underscore the significance of customer satisfaction as a mediator in the relationship between product quality, social media marketing, and brand loyalty in the hospitality industry.

This research aimed to analyze the relationship between electronic human resources (e-HRM) and sustainable competitive advantage, organizational agility and sustainable competitive advantage, and sustainable innovation and sustainable competitive advantage in the manufacturing industry in Indonesia using a quantitative approach. The population of this research was managers of manufacturing companies in Indonesia. A total of 800 online questionnaires were sent using a simple random sampling method and 540 valid questionnaires were received. The questionnaire contains statement items using a Likert scale from 1 to 7. To measure the structural model and to test research hypotheses, the research used the PLS-SEM method with WarPLS 7.0 software. The stages of data analysis in this research were reliability and validity tests, significance tests and hypothesis testing. This research concludes that e-HRM had a positive and significant relationship with sustainable competitive advantage, Organizational Agility had a positive and significant relationship with sustainable competitive advantage and sustainable innovation has a positive and significant relationship with sustainable competitive advantage. The research emphasizes that e-HRM practices encourage sustainable innovation and organizational agility to achieve competitive advantage. The study also provides a more comprehensive understanding that e-HRM practices contribute to sustainable competitive advantage by driving continuous innovation and strengthening organizational agility. The research emphasizes the importance of utilizing digital technology for human resource management (HRM) processes, organizations must implement digital transformation by adopting e-HRM practices to increase manufacturing efficiency and effectiveness thereby increasing performance and competitiveness. This research encourages companies to increase continuous innovation to increase sustainable competitiveness.

This study investigates the effect of marketing via Instagram on Generation Z’s preference for gyms in Jordan, so it would be helpful for marketers of gyms to be aware of using Instagram to attract Generation Z as their potential customers. Moreover, a sample questionnaire was carried out with 138 respondents, which were mostly female respondents (74%) and male respondents (26%). Additionally, 51% of the total number of respondents were 21-24 years old. Therefore, the data was analyzed by applying various statistical techniques such as Cronbach’s alpha for testing the reliability of the data, and multiple regression using SPSS version 22 for examining the hypotheses. Likewise, the results showed that Instagram and these variables (entertainment, interaction, trendiness, and customization) have an effect on customers' brand choice, but trendiness did not have a significant effect on the consumer's brand choice, but after testing the effect of the brand image, it became clear that it has significant effect, and therefore it was concluded that brand image has an important effect on customer’s brand choice.

Arabic handwritten script recognition presents an energetic area of study. These types of recognitions face several obstacles, such as vast open databases, boundless diversity in individuals' penmanship, and freestyle writing. Thus, Arabic handwriting requires effective techniques to achieve better recognition results. On the other hand, Multilayer Perceptron (MLP) is one of the most common Artificial Neural Networks (ANNs) which deals with various problems efficiently. Therefore, this study introduces a new technique called Block Density and Location Feature (BDLF) with MLP, namely BDLF-MLP, which aims to extract novel features from letter images and estimate the letter's pixel density and its location for each equal-sized block in the image. In other words, BDLF-MLP can deal with various styles of Arabic handwritten, such as overlapping letters. The BDLF-MLP starts with the Block Feature Extraction (BFE) of the image by dividing the image into sixteen parts. After that, it calculates the density and location of each block (i.e., BDLF) by finding the sum of all values inside blocks. Finally, it determines the position of the greatest pixel density to obtain better recognition accuracy. The dataset containing 720 images is used to evaluate the efficiency of the proposed technique. Also, 1440 letters are used for training and testing divided evenly between them. The experiment results illustrate that BDLF-MLP outperformed the other algorithms in the literature with an accuracy of 97.26 %.

The goal of this study is to find and analyze the factors that affect teachers' digital competence, consisting of teacher personal characteristics (gender, age, experience, vocational teachers, and attitudes towards technology) and school context (school status, school accreditation, school leadership support, and curriculum support). The research method uses a quantitative approach with a causal design. The study included a total of 444 teachers from vocational high schools (SMK) located in western Indonesia. The characteristics of teachers that influence digital competence are attitudes towards technology and vocational teachers, and this means that teachers who teach vocational subjects have better digital competence than teachers who teach general basic subjects and local content. Curriculum support has a significant impact on vocational school instructors' digital competency. Improved curricular support enhances teachers' digital competence through effective lesson design, execution of teaching and learning activities, and utilization of digital-based practical resources. Meanwhile, age, gender, and school status are not determinants of teacher digital competence. The findings of this investigation recommend that the government, especially the Ministry of Education and the director general of vocational education, include teacher digital competence in evaluating teacher performance and become a consideration for school principals and related offices to improve technology facilities and improve the digital literacy of vocational teachers. This study distinguishes itself from previous research by investigating the determinants that impact teachers’ digital proficiency in vocational education. It specifically considers the influence of school status and vocational school accreditation, taking into account the unique combination of school-based and work-based education with diverse teaching approaches.

This research aims to analyze the relationship between information system quality and user satisfaction, the relationship between perceived usefulness and user satisfaction and the relationship between user satisfaction and sustainable e-learning. The research method used in this research is associative research. The population in this study were all students who had undergone lectures using e-learning. In this study, the analytical model was used, namely Structural Equation Modeling (SEM) and the number of respondents was 456 high school students in Indonesia, who have undergone lectures using e-learning. The sampling technique used in this research is nonprobability sampling. The data collection method used was the questionnaire method and the instrument used to measure this research variable was a 5-point Likert scale. Data processing in this research uses SmartPLS software. The data analysis stage in this research is the outer model test including convergent validity, discriminant validity and composite reliability and inner model analysis, namely hypothesis testing. The results of the study indicate the quality of the information system has a positive effect on user satisfaction, Perceived Usefulness has a positive effect on user satisfaction and user satisfaction has a positive effect on sustainable e-learning. The implication is that every element at every level in formal educational institutions must pay serious attention to personal factors, including attention to student achievement expectations, relative excellence expected by students, student suitability with the e-learning system chosen in an institution's formal education, and the attitude of students who are willing to accept and continuously use e-learning. In this way, students will be consistent in using e-learning so that student achievement, which is the main goal of every school, can be achieved. The limitation of this research is that it does not provide prior understanding to respondents regarding the scope of the meaning of sustainable e-learning.