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181 results on '"Hamadneh, Nawaf"'

1. Student Adoption of E-Learning in Higher Education Institutions in Saudi Arabia: Opportunities and Challenges

Author

Hasan, Asif, Habib, Sufyan, Khan, Mohammed Arshad, and Hamadneh, Nawaf N.

Abstract

This study aims to explore the various factors influencing students in adopting e-learning in educational institutions in Saudi Arabia and analyze the relationship between factors of students' adoption of e-learning and student behavior intention. The study also analyzes perceived opportunities and challenges faced by students in adopting an e-learning system in higher education. A well-structured questionnaire was developed, and information was collected from 509 respondents. The study found that students' behavioral intention to adopt e-learning is highly influenced by performance expectancy, effort expectancy, social influence, facilitating conditions, computer self-efficacy, and internet knowledge. The study confirms the mediating role of student engagement that can act as an alternate path for strengthening the relationship between factors of adoption of e-learning and behavioral intention. In addition, several implications and new lines of investigation are recommended for meeting the educational transformation needs and future sustainability.

Published
2023
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6. Estimating Volatility of Saudi Stock Market Using Hybrid Dynamic Evolving Neural Fuzzy Inference System Models.

Author

Hamadneh, Nawaf N., Jaber, Jamil J., and Sathasivam, Saratha

Subjects
FIXED effects model, RANDOM effects model, DISCRETE wavelet transforms, COST of living, GRANGER causality test, VOLATILITY (Securities)
Abstract

This paper examines the volatility risk in the KSA stock market (Tadawul), with a specific focus on predicting volatility using the logarithm of the standard deviation of stock market prices (LSCP) as the output variable. To enhance volatility prediction, it proposes the combined use of the dynamic evolving neural fuzzy inference system (DENFIS) and the nonlinear spectral model, maximum overlapping discrete wavelet transform (MODWT). This study utilizes a dataset comprising 4609 observations and investigates the inputs of lag 1 of the close stock price (LCP), the natural logarithm of oil price (Loil), the natural logarithm of cost of living (LCL), and the interbank rate (IB), determined through autocorrelation (AC), partial autocorrelation (PAC), correlation, and Granger causality tests. Regression analysis reveals significant effects of variables on LSCP: LCP has a negative effect, and Loil has a positive effect in the ordinary least square (OLS) model, while LCL and IB have positive effects in the fixed effect model and negative effects in the random effect model. The MODWT-Haar-DENFIS model was developed as we found that the model has the potential to be an effective model for stock market forecasting. The results provide valuable insights for investors and policymakers, aiding in risk management, investment decisions, and the development of measures to mitigate stock market volatility. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Double-layer coating using MHD flow of third-grade fluid with Hall current and heat source/sink

Author

Zeeshan, Khan Ilyas, Amina, Alshammari Nawa, and Hamadneh Nawaf

Subjects
double-layer coating, numerical solutions, mathematical modeling, third-grade fluid, hall current, magnetohydrodynamics (mhd) flow, heat source/sink, Physics, QC1-999
Abstract

Multiple coating assessments of fiber optics utilizing micropolar convection non-Newtonian third-order liquid in the existence of Hall effect are examined and executed throughout this academic article. The wet-on-wet (WOW) coating process is used in the research. The fourth Runge–Kutta–Fehlberg algorithm is used to computationally solve the governing equations which dictate the movement of fluid inside the container. In this research, the RK4-Fehlberg algorithm is applied to get numerical results for a list of nonlinear ordinary differential equations (ODEs) describing liquid motion. Pictorially, the contribution of regulating variables on velocity and temperature profiles is examined. It is observed that the velocity profile enhances as the viscoelastic parameter increases and the velocity profile increases for both the non-Newtonian and Hall current increasing parameters in the presence and absence of magnetic parameter M. It is observed that the velocity of the fluid decreases with the increasing values of the Hartmann number m, Brinkman number Br, and magnetic parameter M. Furthermore, the temperature profile increase for BrBr, K, M, and opposite effect is observed for β\beta increases. The suggested approach is compared to homotopy analysis method (HAM) for verification purpose, and excellent agreement is obtained. In addition, as a restricted scenario, a connection is made with the existing literature.

Published
2021
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28. Forecasting Stock Volatility Using Wavelet-based Exponential Generalized Autoregressive Conditional Heteroscedasticity Methods.

Author

Alshammari, Tariq T., Ismail, Mohd Tahir, Hamadneh, Nawaf N., Al Wadi, S., Jaber, Jamil J., Alshammari, Nawa, and Saleh, Mohammad H.

Subjects
HETEROSCEDASTICITY, DISCRETE wavelet transforms, FORECASTING, ERROR functions, MARKET volatility, STOCK exchanges
Abstract

In this study, we proposed a new model to improve the accuracy of forecasting the stock market volatility pattern. The hypothesized model was validated empirically using a data set collected from the Saudi Arabia stock Exchange (Tadawul). The data is the daily closed price index data from August 2011 to December 2019 with 2027 observations. The proposed forecasting model combines the best maximum overlapping discrete wavelet transform (MODWT) function (Bl14) and exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model. The results show the model's ability to analyze stock market data, highlight important events that contain the most volatile data, and improve forecast accuracy. The results were compared from a number of mathematical models, which are the non-linear spectral model, autoregressive integrated moving average (ARIMA) model and EGARCH model. The performance of the forecasting model will be evaluated based on some of error functions such as Mean absolute percentage error (MAPE), Mean absolute scaled error (MASE) and Root means squared error (RMSE). [ABSTRACT FROM AUTHOR]

Published
2023
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44. Student Adoption of E-Learning in Higher Education Institutions in Saudi Arabia: Opportunities and Challenges

Author

Hamadneh, Nawaf, Hasan, Asif, Habib, Sufyan, and Khan, Mohammed

Abstract

This study aims to explore the various factors influencing students in adopting e-learning in educational institutions in Saudi Arabia and analyze the relationship between factors of students' adoption of e-learning and student behavior intention. The study also analyzes perceived opportunities and challenges faced by students in adopting an e-learning system in higher education. A well-structured questionnaire was developed, and information was collected from 509 respondents. The study found that students' behavioral intention to adopt e-learning is highly influenced by performance expectancy, effort expectancy, social influence, facilitating conditions, computer self-efficacy, and internet knowledge. The study confirms the mediating role of student engagement that can act as an alternate path for strengthening the relationship between factors of adoption of e-learning and behavioral intention. In addition, several implications and new lines of investigation are recommended for meeting the educational transformation needs and future sustainability.

Published
2023
Full Text
View/download PDF

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