http://hdl.handle.net/123456789/90 2026-06-02T09:17:20Z http://hdl.handle.net/123456789/221469 Title: The Impact of Product Radicality on Innovation Diffusion: The Mediating Roles of Public Relations Effectiveness and Brand Personality Authors: Ragab, Gehan; Ahmed Moustafa Maree; Hussein EL-Rashidy; Yasser Tawfik Halim Abstract: This study investigates the impact of product radicality on new innovation diffusion, examining the mediating roles of public relations effectiveness and brand personality. Using the 2007 iPhone launch by Apple Inc. as an empirical context, the research explores how radical product characteristics influence market diffusion directly and indirectly through strategic communication and brand perception mechanisms. A quantitative, conclusive descriptive research design was adopted. Data were collected from 509 respondents aged 30 years and above using purposive sampling. A structured online questionnaire was administered, incorporating a video stimulus of the launch presentation to enhance recall accuracy. Data were analyzed using Structural Equation Modeling (SEM) via SmartPLS 4 to test direct, indirect, and mediation relationships. The findings reveal that product radicality has a significant positive effect on innovation diffusion, brand personality, and PR effectiveness. PR effectiveness significantly influences both brand personality and innovation diffusion. Brand personality emerges as a strong predictor of innovation diffusion. Mediation analysis confirms that PR effectiveness and brand personality mediate the relationship between product radicality and innovation diffusion. The model explains 63.5% of the variance in innovation diffusion. This study contributes to innovation diffusion theory by integrating public relations and brand personality into a mediation framework. It advances theoretical understanding by positioning PR effectiveness as a strategic mechanism that amplifies the market impact of radical innovations. Findings provide actionable insights for managers launching radical products, emphasizing the importance of aligning product radicality, PR execution, and brand personality to accelerate market diffusion 2026-01-01T00:00:00Z http://hdl.handle.net/123456789/221383 Title: A Novel Hybrid ANFIS-NARX and NARX-ANN Models to Predict the Profitability of Egyptian Insurance Companies Authors: Hanaa H. A. Aboul Ela; Hanaa Hussein Ali Aboul Ela Abstract: The use of fuzzy logic models with machine learning (ML) models have become common in many areas, especially insurance field. This study aims to compare between non-hybrid models such as artificial neural network (ANN) model, nonlinear auto-regressive with exogenous inputs (NARX) model, and the following hybrid models adaptive neural fuzzy inference system (ANFIS) model, (ANFIS-NARX) model and (NARX-ANN) model to predict the profits of the insurance activity which represent the important indicator of the good performance of Egypt’s 39 insurance companies in the period from 1st January 2009 to 31 December 2022 per month. This prediction based on the following factors (net premiums (NP), reinsurance commissions (RC), net income from investments (NIFINV), net compensation (NC), commissions of production cost (CPC), general and administrative expenses (GAE),that help decision makers to make appropriate decisions. The results found that the(ANN) model is given good results compared with the following models (ANFIS), (NARX), hybrid (ANFIS-NARX) and (NARX-ANN) models according to the following prediction accuracy measures (RMSE, MAPE, MAE and Theil Inequality). The explanatory ability criterion (R2 ) was appeared (0.79, 0.61) respectively for training and testing phases in persons insurance companies. The explanatory ability also was appeared(0.83, 0.68) respectively in property insurance companies. 2024-11-01T00:00:00Z http://hdl.handle.net/123456789/221382 Title: Statistical Models to Measure the Impact of Intellectual Property Rights Protection on Foreign Trade in Egypt Authors: Hanaa H. A. Aboul Ela; Hanaa Hussein Ali Aboul Ela Abstract: This study aims to estimate the relationship between the Protection of intellectual property rights indices and the foreign trade index in Egypt from 1995 to 2022. The comparison has been made between many models such as the fully modified ordinary least squares (FMOLS) model, dynamic ordinary least squares (DOLS) model, Canonical co-integration regression (CCR) model, and auto-regressive distributed lag (ARDL) model. The results of the study showed that the best model was the ARDL model to increase its explanatory ability. The study also showed that the most important property rights protection indicators affecting the foreign trade index are the number of applications and registrations of brands, the number of patents registered and granted, the number of applications and registrations of industrial designs, and the proportion of expenditure on research and development as a proportion of gross domestic product (GDP). The estimated model also passed all diagnostic tests and showed that there was no auto-correlation and no Heteroskedasticity. In addition, it was found to follow a normal distribution and to be stable. 2024-01-01T00:00:00Z http://hdl.handle.net/123456789/221381 Title: Forecasting Emissions of Carbon Dioxide (CO2), Methane (CH4) and Energy Consumption in Egypt Using VECM and ARIMAX Models Authors: Hanaa Hussein Ali Aboul Ela Abstract: Greenhouse gas emissions are one of the important environmental problems in Egypt that do not harm only humans, but also contribute to climate changes all over the world. The emissions of carbon dioxide (CO2) and methane (CH4) are the most important of these emissions. The decision makers seek to use renewable energies to reduce greenhouse gas emissions. Therefore, this paper aims to measure the factors affecting CO2 and CH4 emissions in Egypt during the period from 1980 to 2019 and to predict of these emissions and energy sources from 2020 to 2030. The study applied the Vector Error Correction Model (VECM) and Autoregressive Integrated Moving Average with Exogenous variables (ARIMAX) models. The study results found that the most influential variables on CO2 gas emissions are energy consumption, gross domestic product, and international trade. It was also found that livestock production, energy consumption and agricultural fertilizers are the most influential variables on CH4 emissions. It was also found that the predictability of VECM is better than the ARIMAX model, so we can use it to predict emissions of CO2 and CH4. 2023-09-01T00:00:00Z