An Evaluation of the Performance of Higher Educational Institutions using Data Envelopment Analysis: An Empirical Study on Algerian Higher Educational Institutions

The aim of this research paper is to clarify to evaluate the performance of the Algerian institutions of higher education using data envelopment analysis method based on the concept of benchmarking Five indicators of inputs as well as outputs that reflect three dimensions of teaching learning and scientific research were used were used total number of students enrolled in graduation total number of students enrolled in post-graduation permanent professors graduated students and scientific publications The findings of data envelopment analysis pointed out that there is a significant variation in the performance of the Algerian institutions of higher education in favor of the academic years It was highlighted that inefficient internal processes or poor conditions surrounding these processes were the main causes of the weak performanc

Using the Linear Discriminant Analysis Method to Classify Types of Bowels and Esophageal cancer in Jordan

The research aims at achieving the best linear model to distinguish between two types of Bowels and Esophageal cancer in Jordan, using the methodofdiscriminant analysis, the SPSS program was used to analyze the data. The study concluded a number of results, the most prominent of which were: the variables sex (x1), weight (x3), and Platelets Count P.C (x8) which have a significant impact in constructing the discriminatory function. The probability of correct classification of a disease belonging to the first group was equal to (62.8%) and to the second group was equal to (77%). The probability of misclassification in the first group, was equal to (37.2%), and for the second group was (23%), the overall correct classification ratio (71.6%) and the false classification ratio (28.4%),the probability of correct classification of a disease belonging to the first group was equal to (66.4%) and the second group was equal to (77.6%). It was noted that the discriminant analysis method was able to identify the most important independent variables in the diagnosis of both types of Bowel and Esophageal cancer

Forecasting the Number of Traffic Accidents in Jordan using the Poisson Regression Model

The study aims at forecasting the number of traffic accidents in Jordan for the year 2022, based on the monthly data related to traffic accidents for the period (2017–2021) using the Poisson regression model. SPSS version 26 and Minitab version 19 data analysis programs were used to analyze the collected data. The study concluded that the use of the Poisson regression model is very appropriate to forecast the number of traffic accidents during the next period of time. The Poisson regression method is a useful method for estimating and forecasting. The researchers recommend adoption of this technique in related studies, conducting more extensive studies on the Poisson regression model, and reconsidering the current legislation and the penalties related to traffic accidents

The effect of big data on financial reporting quality

The current manuscript aimed to explain the impact of big data on the financial reporting quality of the industrial sector in Jordan. To achieve the manuscript goals and validate hypotheses, a field study was conducted by distributing a questionnaire to 325 financial managers in industrial companies listed on the Amman Stock Exchange during a specific period. Gathered data were analyzed using structural equation modeling (SEM). The manuscript concluded that the big data dimensions, including variety, volume, and velocity, had a positive impact on financial reporting quality. Therefore, a set of recommendations were provided to managers of the industrial companies in Jordan to put in place an extensive data governance system to as-sure data quality, security, privacy, and compliance. To ensure the integrity and dependability of financial reporting, define data ownership, create data quality standards, and develop processes for data access, use, and preservation

Remote work arrangement: An investigation on the influence of team’s innovative performance in multinational NGOs in Jordan

As the workforce worldwide goes through a transformative shift towards remote work, this paper discusses the positive effects of this quite flexible work arrangement on team’s innovation performance (TIP) in multinational, non-governmental organizations (NGOs). Adopting cross-sectional, quantitative research design, empirical data were collected through a survey of 268 employees of multinational NGOs operating in Jordan. The collected data were, then, analyzed using structural equation modeling. The results of the analysis showed that remote work has significant, positive effects on TIP in NGOs. Of the various remote work features investigated, spatial flexibility has the highest effect. The study results contribute to the ongoing discourse on the future of the work styles and have implications for leaders, policymakers, and practitioners who seek promoting innovation in multinational NGOs

Nursing Perspectives on the Association between Human Capital Development and the Work Engagement: A Cross-Sectional Study

This study examined the impact of human capital development on the nurses’ work engagement. A questionnaire was adapted and distributed to a nursing convenience sample in different types of hospitals. The sample size was 286 male and female nurses who completed it. Structural Equation Modelling (SEM) was used to test the research hypothesis. Results revealed that human capital development had a direct impact on the nursing work engagement. Nursing work engagement give managers ability to improve the work environment, increase the work professional and institutional loyalty. Supporting the human capital development tools is very important for any healthcare organization

Artificial intelligence in Jordanian education: Assessing acceptance via perceived cybersecurity, novelty value, and perceived trust

The growing significance of Artificial Intelligence (AI) across different fields highlights the essential role of user acceptance, as the success of this technology largely depends on its adoption and practical use by individuals. This research aims to examine how perceived cybersecurity, novelty value, and perceived trust affect students' willingness to accept AI in educational settings. The study's theoretical basis is the AI Device Use Acceptance (AIDUA) model. Using structural equation modeling, the study tested hypothesized relationships using data from 526 students at Jordanian universities. The results showed that social influence is positively associated with performance expectancy, while perceived cybersecurity is positively related to both performance and effort expectancy. Novelty value is positively associated with performance expectancy but a negative one with effort expectancy. Additionally, effort and performance expectancy significantly influence perceived trust and the willingness to accept AI. Moreover, perceived trust has a notable positive effect on the willingness to accept AI in education. These findings provide valuable guidance for the creation and improvement of AI-driven educational systems in universities, contributing to the broader understanding of AI technology acceptance in the educational field

Determinants of behavioral intention to use big data analytics (BDA) on the information and communication technologies (ICT) SMEs in Jordan

Big Data Analytics (BDA) provides an important resource for businesses seeking to enhance their performance and gain a competitive advantage, although not all organizations are adopting BDA techniques, and small and medium-sized enterprises (SMEs) in Jordan have been slow in this regard, despite being key players in any healthy economy, and the fact that BDA adoption can be facilitated by using the Technology Acceptance Model (TAM). The purpose of this study is to investigate the drivers of behavioral intention among managerial-level employees in Jordanian ICT SMEs to adopt BDA through a quantitative correlational research approach. The TAM questionnaire was used to gather data from 271 online survey participants in Jordan using Google Forms. The target group included management level staff working in small and medium-sized ICT firms (SMEs). Confirmatory factor analysis (CFA) was used to evaluate the research instrument's reliability and validity, and structural equation modeling (SEM) was utilized to test the study's hypotheses. The findings revealed that perceived usefulness, perceived ease of use, and perceived “privacy and security” significantly influenced managerial-level employees' behavioral intention to use BDA in their organizations. The research findings also supported the application of TAM, and the results of the investigation indicated that managerial-level employees would be willing to use BDA techniques providing they were perceived to be useful, user-effortless, and posed little concern about privacy and security. Overall, the current study's results demonstrate that the suggested model had good predictive power, 51% of the variance in behavioral intention, and was therefore capable of predicting managers' intentions to use BDA

Common variants in toll-like receptor family genes and risk of gastric cancer: a systematic review and meta-analysis

Background: An increasing number of studies have suggested the relationship between single-nucleotide polymorphisms (SNPs) in toll-like receptor (TLR) genes and gastric cancer (GC) susceptibility; however, the available evidence is contradictory. This meta-analysis aimed to comprehensively evaluate whether the SNPs within the TLR family are related to GC development.Methods: PubMed, Scopus, and China National Knowledge Infrastructure (CNKI) were systematically searched up to May 2023 to obtain the pertinent publications. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were applied to examine the associations using the random-effects model.Results: A total of 45 studies with 25,831 participants (cases: 11,308; controls: 14,523) examining the relation of 18 different SNPs in the TLR family to GC were analyzed. Variations in TLR-4 rs4986790, TLR-4 rs4986791, TLR-5 rs5744174, and TLR-9 rs187084 were significantly associated with increased risk of GC in different genetic models. No significant association was detected for TLR-2-196 to -174de (Delta22), TLR-2 rs3804100, TLR-4 rs11536889, TLR-4 rs11536878, TLR-4 rs2770150, TLR-4 rs10116253, TLR-4 rs1927911, TLR-4 rs10983755, TLR-4 rs10759932, TLR-4 rs1927914, and TLR-10 rs10004195.Conclusion: These findings indicate that variations in TLR-4, TLR-5, and TLR-9 genes were found to be potential risk factors for GC

A Novel Microstructure of 2-Bit Optical Analog to Digital Converter Based on Kerr Effect Nonlinear Nanocavities in 2D Photonic Crystal

In this paper, an all-optical analog-to-digital converter based on nonlinear with silicon materials is designed and simulated. The proposed structure consists of three nonlinear nanocavity that control the optical signal power intensity. The nonlinear material used is aluminum gallium arsenide (AlGaAs). Aluminum gallium arsenide (AlGaAs) with a linear refractive index of n0=1.4 and a nonlinear refractive index of n2=1.5×10−17. Due to the small path length of the waveguides, the optical signals move a short distance and as a result, the power optical losses along the path are reduced and on the other hand, the speed of the structure is increased. The transmission percentage is between 90% and 100%. The overall dimensions of the structure are 324 μm2. The plane wave expansion (PWE) method is used to calculate the band structure. The two-dimensional finite difference time domain (2D-FDTD) method is used to calculate the transmission power spectrum and the simulation results