The evolution of technology and the widespread adoption of smart mobile devices like smartphones and tablets have significantly altered tourists' behavior using tourism services. Based on The Unified Theory of Acceptance and Use of Technology, this research aims to investigate the factors affecting Gen-Y's inclination to use tourism apps in Vietnam. The model was tested using structural equation modeling (SEM) in quantitative methodology with 337 users from Vietnam. The result showed that five factors positively impact the intention behavior of using mobile tourism applications: performance expectancy, effort expectancy, social influence, trust, and perceived security. Moreover, the findings propose practical implications and provide valuable insights for tourism app developers, marketers and operators in developing more effective tourism apps.

The rapid progress of TICs has generated different ways to modify and transfer information, which implies the generation of new forms of knowledge. The objective of this study is to establish the relationship between digital competencies and university teaching performance in public higher education in Huancayo. The study is of a basic type with a quantitative approach and correlational level, developed with the partition as a sample of 272 teachers and 387 students who develop teaching-learning activities at the UNCP. The data were analyzed and modeled through structural equations based on PLS. The research arrived at the following results: a value of 0.890 in Spearman's Rho correlation coefficient and a significance level of .000, which shows that there is a high positive relationship between the study variables; likewise, the hypothesis is accepted. general which considers that there is a significant relationship between digital competencies and teaching performance in the classroom.

The classification of large-scale textual dataset is associated with a huge number of instances and millions of features which must be discriminated between large numbers of categories. The task requires the utilization of a defined hierarchy structure and tools that automatically classify instances within the hierarchy known as Large Scale Hierarchical Text Classification (LSHTC). Predicting the labels of instances by the employed classifiers is challenging due to the high number of features. Furthermore, the existing Dimensional Reduction (DR) approaches in cooperation with the LSHTC framework are still quite inefficient. In such a problem, an effective Hierarchical Dimensional Reduction approach can be advantageous in improving the performance of the LSHTC. Therefore, in this paper, we enhance the performance of LSHTC by proposing a Multi-stage Hierarchical Dimensional Reduction (MHDR) approach based on Modified Feature Hashing (MFH) and Hierarchical Bi-Filtering (HBF) method. In addition to alleviating bad collision and result discrepancy, experimental results show that the proposed approach has achieve the best performance in terms of micro-f1 and macro-f1 by recording average scores of 58.47% and 54.77% using TD-SVM, and average scores of 51.14% and 48.70% using TD-LR, respectively. The method also achieved 11% speed-up than the approaches compared.

Potential international students use social media platforms to acquire important information about schools and their brand reputations while making international higher education decisions. By means of a cross-sectional data from 384 international students at three universities in North Cyprus, the study aims to explore the relationship between social media engagement, information credibility and enrolment intention. Furthermore, if information credibility works as a mediator between social media engagement and enrollment intention, and the moderating role of student type. The study makes several contributions to the literature review and its recommendation helps top management at universities and policy makers in North Cyprus to pay attention to the role of social media in recruiting international students. The findings of this study indicate that credibility fully mediates the relationship between social media engagement and enrollment intention, but student type doesn’t moderate the relationship between information credibility and enrollment intention. The limitations and future studies are discussed in this study.

This study investigates the mediating role of competitiveness in the relationship between FinTech adoption and banking performance in the Middle Eastern region. A quantitative research design is employed, utilizing survey data from banking professionals across multiple countries. The data is analyzed using PLS-SEM modelling. The results show a positive and statistically significant impact of FinTech integration on the competitiveness of financial institutions and the performance of banks. On the other hand, the mediation of competitiveness is involved in the process of FinTech adoption and bank efficiency, suggesting that banking institutions that can utilize FinTech advantageously have greater chances of translating the benefits of FinTech adoption into better performance. This study supports the literature by providing a practical example of the use of FinTech as a factor for competitiveness and improving the performance of banks in the Middle East. These findings have huge managerial and practical implications and can help large banks gain competitive advantage and effectively integrate FinTech platforms to achieve real improvements. The value of this research is that it fills the gap in the existing literature, i.e. the role of competition as a mediating factor. By combining studies on competitive strategy approaches with those on technological innovation theory, this study combines a complete worldview related to the performance of banks in the digital age.

This research aims to analyze the influence of e-leadership behavior on employee commitment at the immigration office, the influence of the e-Work Environment on employee commitment at the immigration office, and the influence of e-Job satisfaction on employee commitment at the immigration office. The research method used in this research is associative research. Associative research is research that aims to determine the relationship between two or more variables. In this way we can build a theory that functions to predict and control a phenomenon. The population in this study were all immigration office employees. In this research, an analysis model is used, namely Structural Equation Modeling (SEM). The respondents for this research were 678 immigration office employees who were determined using a simple random sampling method. Research data was obtained by distributing online questionnaires via social media. The instrument used in this research uses a Likert scale 7 scale. The data analysis stage of this research is testing the outer model and inner model. The outer model test consists of convergent validity, discriminant validity and composite reliability and the inner model test, namely hypothesis testing or significance testing. The results of data analysis show that e-leadership behavior has a positive and significant relationship to employee commitment at the immigration office, the e-Work Environment has a positive and significant relationship to employee commitment, and e-Job satisfaction has a positive and significant relationship to employee commitment at the immigration office.

This study explores the factors affecting CliQ payment service adoption in Jordan as it represents a major shift in the Jordanian market to Fintech and mobile marketing. This study presented a distinctive model by integrating the “unified theory of acceptance” and the “technology acceptance model” TAM with the “use of technology UTAUT” to measure the behavioral intention of consumers and the satisfaction of the users towards utilizing the CliQ service. The study measured the linkage between four predictors (perceived usefulness, social influence, perceived ease of use, and financial risk) as well as both utilizers’ intention to CliQ service usage and utilizers’ satisfaction with using the service, along with observing the association between these predictors to determine their contribution to the users’ satisfaction mediated by the users’ intention to utilize the service mentioned above. A survey instrument was distributed to 604 respondents, and it was developed and validated by academics, as a pilot test. As well as a pre-test. Hypotheses were tested with multiple linear regression analysis using SmartPLS software to interpret path coefficients, and reliability and validity within the outer model were tested through correlation analysis. Additionally, internal consistency was explored by applying Cronbach’s alpha. The outcomes proved that the predictors significantly affect both utilizers’ behavioral attitudes and satisfaction with using the CliQ service, except for financial risk. The data analysis also indicated a significant indirect influence of all the independent variables on utilizers’ satisfaction through behavioral intention to utilize the CliQ service, except for financial risk, which had an insignificant indirect influence on utilizers’ satisfaction through behavioral intention for service usage. The findings of the current article close the gap found in the literature concerning measuring usability to enhance user satisfaction and adoption of Fintech services. Therefore, bank managers and policy planners can find insights for developing and improving mobile banking apps.

With flexible learning, students are actively engaged in their own education and are held to high standards of performance. Online academic courses make it easier for students to receive personalized education because they provide students with more flexibility to concentrate on what is most important to them and give them greater control over their own education. This study’s objective was to investigate whether there is a correlation between how well students succeed in online classes and the extent to which they make use of the schedule and the geographical and resource flexibility offered by such programmes. This article uses a developing approach for predicting and classifying the flexibility in online learning of students who are at risk of failing due to academic and demographic variables. The K-nearest neighbours (KNN) method, the random forest (RF) method, and the logistic regression method were used to categorise the students participating in flexible online learning. The information for the dataset came from Kaggle, and it was gathered for use in testing machine learning. The dataset had a total of 1,875 instances representing 11 different features. Also, accuracy, precision, sensitivity and f-score metrics were applied to evaluate the system. The results show that the RF algorithm has a high accuracy percentage of 85%. The empirical findings demonstrate that students formed distinct patterns of learning time, location and access to knowledge. This suggests that flexibility was used to a significant degree. Patterns in learning time and the availability of learning materials were shown to have a substantial relationship with the accomplishments of the students. Understanding flexibility use habits may help adapt lessons and boost collaboration among similar students.

This study attempts to study the impact of the moderating role of internal audit between cloud accounting and limiting creative accounting practices in commercial banks. The study utilized a descriptive and analytical approach. The target population of this research consists of all employees of the 13 Jordanian commercial banks listed on the Amman Stock Exchange, while the number of employees in commercial banks is (22,407) employees. This led to the use of a simple random sample of (400) employees. The results found that there is a positive effect of the moderating role of internal audit on the impact of cloud accounting on reducing creative accounting practices in commercial banks. The study suggests that future studies should give recommendations and proposals to improve and develop cloud accounting and internal auditing in commercial banks, increase transparency, monitoring and compliance in accounting and financial operations, and reduce the risks associated with cloud accounting and creative accounting practices.

Social cybernetics, as an interdisciplinary field, has gained increasing interest in the last decade due to the influence of information technologies in society through connectivity, Internet of things, process automation, artificial intelligence among others. This research focuses on exploring the relationship between social cybernetics (communication and control mechanisms) based on information technologies and local development, using structural equation modeling as an analytical tool. The design was non-probabilistic, with a sample of 482 people. The independent variables under study were Use of ICT for communication between local authorities and the population (CAP), Use of ICT for collaboration between public and private institutions (CPPC), Use of ICT for shared decision making (SDM), Use of ICT for local development planning (LDP) and Use of ICT for knowledge management (KM); and the dependent variable was Local Development (LD). It was determined that there is a relationship between all of them except with CAP. The direction and magnitude of the other ratios were: + 0.1390; - 0.3661; + 0.4472 and + 0.8432 respectively. The coefficient of determination (R2) was 93.69% facilitating the prediction of future results. The model has an adequate fit.