During the COVID-19 pandemic, educational institutions were shut down all over the world, which impacted over 60% of students and caused a massive disruption of the education system. The goal of this paper was to identify the critical success factors for E-learning during COVID-19 using the multi-criteria Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) techniques to enhance the educational process. Data were generated by interviewing 69 E-learning managers in educational institutions during COVID-19 based on defined evaluation criteria and E-learning approaches through several channels. We found that technology management, support from management, increased student awareness to use E-learning systems, and demanding a high level of information technology from instructors, students, and universities were the most influential factors for E-learning during COVID-19. Among the five learning systems, blended learning was the most suitable learning system to practice. These results demonstrated that, regardless of how extraordinary the technology is in an educational institution, the readiness of E-learning execution played a large role in boosting the educational process during the COVID-19 pandemic.

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Sensor embedded products utilize sensors implanted into products during their production process. Sensors are useful in predicting the best warranty policy and warranty period to offer a customer for remanufactured components and products. The conditions and remaining lives of components and products can be estimated prior to offering a warranty based on the data provided by the sensors. This helps reduce the number of claims during warranty periods, determines the right preventive maintenance (PM) policy, and eliminates unnecessary costs inflicted on the remanufacturer. The renewing, one-dimensional Free Replacement Warranty (FRW), Pro-Rata Warranty (PRW), and combination FRW/PRW policies' costs for remanufactured products and components were evaluated with/without offering PM for different periods in this paper. To that end, the effect of offering renewable, one-dimensional, Free Replacement Warranty (FRW), or Pro-Rata Warranty (PRW), or combination FRW/PRW warranty policies for each disassembled component and sensor embedded remanufactured product was examined, and the impact of sensor embedded products on warranty costs was assessed. A case study and varying simulation scenarios is examined and presented to illustrate the model's applicability.

Financial technology (FinTech) has emerged as a significant financial sector breakthrough due to the sharing economy, new legislation, and IT advances, contributing to its fast growth. Under a new national policy, Saudi Arabia intends to increase the number of FinTech firms. Thus, it is necessary to develop a more profound understanding of what critically enables FinTech innovation, how these enablers are interconnected, and their priorities. This research study aims to identify and model the critical enablers of FinTech innovation by exploring contextual relationships among them and their importance. A hybrid approach was followed using interpretive structural modeling (ISM) and an analytic network process (ANP) to achieve the objective. Eleven enablers and their essential components were extracted from the literature and confirmed by Saudi FinTech experts who provided input data on their linkages and relative importance through interviews and a designed questionnaire. The developed model reveals the enablers’ structure in terms of their driving and dependence powers and classifies them into six levels with relative importance to each other. The developed model in this research puts forward a holistic perspective on FinTech and innovation, assisting decision-makers, regulators, policy designers, practitioners, and technology developers to create effective ways to safeguard the FinTech industry’s growth.