Pandemic moments have generated mental and emotional problems in students at all levels. These have been affected by the format of virtual classes, the mandatory confinement and the little physical relationship due to the existing restrictions, generating academic burnout and anxiety in university students. In this context, the objective was to know the existing relationship between burnout and anxiety in students of the FIS-UNCP, the 15-question Maslach Burnout Inventory Student Questionnaire (MBI-SS) was used with the dimensions: Emotional Exhaustion, Cynicism and Loss of Academic Efficacy and 5 questions to know the level of technological anxiety or technostress, with a population of 328 university students of 10 semesters, through the questionnaire in Office Forms. The research design was non-experimental, transectional, with a qualitative-quantitative approach and descriptive-explanatory levels. The descriptive data analysis was made based on the scale, allowing the identification of students with burnout and the structural equation modeling facilitated the establishment of the relationship between the variables. The study showed that 26 students (7.93%) suffer from academic burnout. At the same time, it has been demonstrated that there is a positive and significant relationship between emotional exhaustion and lack of academic efficacy, with technological anxiety with path values of 0.701 and 0.345 respectively, the p-values allowed demonstrating hypotheses 1 and 3 formulated. At the level of the structural model, it allows anticipating future results, since the coefficient of determination (R2) calculated was 0.838.

One time series model developed to predict economic data is Spatial Vector Autoregressive with Exogenous Variables (SpVARX). This model can accommodate simultaneously the interrelationships between variables, the impact of exogenous variables, and Inter-regional linkages. However, this model has not adjusted the nonlinearity relationships between variables. The relationship between economic variables is usually not linear. Therefore, we introduce the Threshold Spatial Vector Autoregressive with exogenous variables (TSpVARX). This paper assesses the forecasting performance of TSpVARX and compares it with SpVARX models. We conducted a simulation study by generating 100 times the simulation data with twelve scenarios. We found that the forecasting performance of the TSpVARX model is better than SpVARX when there is a nonlinear relationship between variables. In addition, we find that the forecasting performance of TSpVARX models will improve as the sample size increases.

Research on human-computer interaction currently focuses on enhancing system usability by establishing an appropriate user interface (UI) that depends on users’ features. Online users typically have different perceptions of their favored interface design depending on their preferences. Thus, those interface preferences could be utilized to recognize online users’ identities. User authentication is another critical issue that should be considered to improve online security mechanisms without compromising usability. This study investigates the feasibility of using UI preferences as evidence of user identity. The proposed method applies to the design preferences of users dealing with online systems (e.g., e-exam and e-banking). These preferences are closely associated with individual characteristics, whether physical, cognitive, psychological, psychomotor, demographic, or experience based. Many design characteristics could be used in online systems; for example, the e-exam interface design may use features such as the font (size, color, and face), the number of questions per page, background color, questions group, timer type, and sound alert. The feasibility evaluation of this study indicated that 96.8% of research participants have variations in their preferences, and each participant kept 94.5% of their design preferences throughout different sessions.

This study aims to examine the role of electronic human resource management (E-HRM) in contemporary organizational excellence in Jordan Social Security Corporation (SSC) to understand how SSC organizational excellence was impacted by E-HRM in Jordan. A questionnaire was created and delivered to 100 employees in the institution to complete this study. Out of this distribution, 82 usable questionnaires were retrieved for the purpose of analysis. The findings revealed that there was a significant statistical relationship between all functions of E-HRM and organizational excellence. Moreover, the findings revealed that Jordanian social insurance companies should expand the use of E-HRM to attain organizational excellence in all areas. Discussion, conclusion, and future work are depicted at the end of this study.

This study investigates how knowledge-oriented leadership impacts on innovation performance both directly and indirectly mediated electronic based knowledge management systems (e-based KMS). Where, electronic knowledge management system consists of knowledge management infrastructures, and knowledge management processes. Primary data was obtained through a questionnaire given to 110 managers or directors of the manufacturing company as respondents. In addition, data were also obtained through observation techniques, and interviews with respondents. Both descriptive statistical analysis, and structural equation modelling (SEM) was used as an analysis method. The findings suggest that knowledge-oriented leadership has a positive, direct, and significant influence on knowledge management infrastructures as well as knowledge management processes. However, knowledge-oriented leadership has no direct influence on innovation performance. The findings also indicate that electronic knowledge management systems that consist of knowledge management infrastructures, and knowledge management processes have a direct, positive, and significant influence on innovation performance. This study suggested that there are two key pathways for businesses to improve their innovation performance i.e.: enhancing the technological, cultural, and structural infrastructure of the company, and enhancing knowledge creation, use, and utilization.

This paper aims to examine the mediating effect of attitude toward the continued application of e-tax in the association between perceived usefulness, ease of use, compatibility, and intention to continue applying e-tax based on empirical evidence from Vietnamese tax officials. Thereby, the research model is proposed and the hypotheses are developed on the basis of the Technology Acceptance Model (TAM). This study applies a quantitative analysis with a research sample of 343 tax officials from tax authorities at all levels within Vietnam. This study applies stratified and convenient sampling techniques. Structural equation modeling with AMOS was used to test the hypothesized relationships. The results revealed that among perceived usefulness, ease of use, and compatibility only perceived usefulness has a direct impact and positive relationship to the intention to continue applying e-tax and the attitude toward the continued application of e-tax also has a direct impact and positive relationship to the intention to continue applying e-tax. Especially, the results prove the mediating effects of attitude toward the continued application of e-tax on the relationships towards the intention to continue applying e-tax. This study contributes to both the literature and practice. The limitations and future research implications are discussed.

The mobile services sector in Saudi Arabia has experienced significant growth in recent years, largely driven by the increasing demand for mobile communication and internet services. This systematic review aims to identify and evaluate the effective strategies for enhancing customer satisfaction in Saudi Arabia's mobile services sector. A systematic review was conducted across five databases from 1st January 2010 and 31st March 2023. The entire process was followed as recommended by the PRISMA guidelines. The findings suggest that the most effective strategies for enhancing customer satisfaction in the Saudi Arabian mobile services sector are improving network coverage, enhancing customer service, offering competitive pricing, introducing new technology and features, and providing value-added services. By adopting these strategies, mobile service providers in Saudi Arabia can enhance their customers' satisfaction, build stronger relationships with their customers, and ultimately increase customer loyalty. Moreover, the study revealed that a combination of these strategies would lead to higher levels of customer satisfaction. The study's findings indicate that mobile service providers in Saudi Arabia can enhance customer satisfaction by focusing on various strategies, such as improving network coverage, customer service, pricing, technology, and features, and providing value added services. Customer satisfaction is one of the main aspects of service delivery. Immediate measures in this regard will assist the mobile sector in Saudi Arabia to plan effective approaches to improve customer satisfaction; this, in turn, can give them a competitive edge in the market and sustain growth in the mobile services sector.

This study examines the impact of Digital Zakat Management, Transparency in Zakat Reporting, and the Zakat Payroll System on Zakat Growth Acceleration, with Zakat Management Accountability as the mediating factor. Data from muzakki and Zakat institutions were collected through surveys and questionnaires, and regression and correlation analyses were used to assess the relationships between variables. The findings reveal that digital Zakat management positively impacts Zakat management accountability and Zakat growth acceleration. Transparency in Zakat reporting also has a positive effect on Zakat management accountability. However, the Zakat payroll system does not significantly influence Zakat management accountability or Zakat growth acceleration through mediation. The study underscores the importance of accountability as a mediator between digitalization, transparency, and Zakat growth, offering insights for Zakat institutions to optimize their practices and promote equitable social impact. Future research should consider qualitative methods and comprehensive variables to understand Zakat dynamics better.

This study employs a quantitative approach to investigate the relationship between E-learning and Organizational Excellence in UAE universities. The study focuses on 250 senior and middle administrators from public universities selected through a convenience sampling method. The advanced statistical tools SPSS and AMOS were used to analyze the research data through Structural Equation Modeling (SEM). The findings reveal the impact of e-learning dimensions–Technical Knowledge and Management Willingness—on Organizational Excellence. Additionally, the study delves into moderation effects, revealing that Gender, Age, Educational Level, and Experience play pivotal roles in influencing perceptions of e-learning among senior and middle administrators at UAE public universities. This research contributes to the understanding of how e-learning impacts Organizational Excellence within the UAE university landscape while also highlighting the crucial moderating roles of demographic variables. These findings offer valuable insights for educational institutions aiming to optimize e-learning strategies and enhance organizational performance.

Explosive material detection considers the identification and classification of explosive materials using techniques from traditional sniffer dogs to cutting-edge sensing technology like thermal imaging, X-ray scanners, and chemical sensors. Explosive detection is applied in various locations, including airports, government buildings, and public areas, to prevent terrorist attacks and criminal actions that attempt to employ explosive devices. The effectiveness of these procedures is dependent on the detection materials, equipment, and environment, so new techniques are continuously explored to increase precision, sensitivity, and detection speed. Because explosive substances present a critical risk to infrastructure, security, and public safety, extensive analysis of existing detection methods is needed. This paper highlights key areas for further research and development in explosive materials detection by addressing identified limitations and challenges. Specifically, advancements in technology, interdisciplinary collaboration, and the integration of AI techniques offer significant opportunities for improving detection accuracy, reducing false positives, and ensuring safer environments for individuals and society.