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.

This study presents a hybrid multicriteria decision-making approach for evaluating stocks in the Saudi Stock Market. The objective is to provide investors and stakeholders with a robust evaluation methodology to inform their investment decisions. With a market value of USD 2.89 trillion dollars in September 2022, the Saudi Stock Market is of significant importance for the country’s economy. However, navigating the complexities of stock market performance poses investment challenges. This study employs the best–worst method and the technique for order preference by similarity to identify an ideal solution to address these challenges. Utilizing data from the Saudi Stock Market (Tadawul), this study evaluates stock performance based on financial criteria, including return on equity, return on assets, net profit margin, and asset turnover. The findings reveal valuable insights, particularly in the banking sector, which exhibited the highest net profit margin ratios among sectors. The hybrid multicriteria decision-making-based approach enhances investment decisions. This research provides a foundation for future investigations, facilitating a deeper exploration and analysis of additional aspects of the Saudi Stock Market’s performance. The developed methodology and findings have implications for investors and stakeholders, aiding their investment decisions and maximizing returns.

Universities worldwide strive to achieve excellence in research, learning, teaching, and community services, which are the pillars of their strategic plans. However, satisfying international ranking criteria might not directly result in achieving their strategic objectives. This paper proposes a new approach to rank university colleges by evaluating their educational quality. Standard sets of criteria from multiple international university ranking systems and a university’s strategic plan’s Balanced Scorecard perspectives were cross-mapped for the evaluation. A new multi-criteria decision-making-based framework was applied to six colleges of a non-profit university in the Middle East. It revealed their performance rankings and contributions to the university’s educational quality objectives. This paper offers a novel approach for universities to develop strategies that satisfy multiple international ranking systems while achieving their strategic goals concurrently and as per their priorities. Implications include informing university leaders on the most contributing colleges and assisting in pinpointing quality shortcomings and their causes. This helps universities design better performance indicators and allocate resources to achieve educational excellence. This paper puts forward a new approach for universities to unify their efforts in satisfying the requirements of multiple international ranking systems while achieving their strategic goals.

The COVID-19 pandemic has impacted the financial performance of companies in different sectors. One of the most important sectors affected is the energy sector. Therefore, this research study aims to conduct a financial performance evaluation of companies in the Saudi energy sector in 2019, 2020, and 2021. This is to capture and analyze the effect on companies before, during, and post the COVID-19 pandemic, respectively. A hybrid multicriteria decision-making (MCDM) approach is followed to achieve the objective. The financial performance evaluation of energy companies is based on four financial dimensions and 11 performance indicators. Results revealed that energy companies’ efficiency and profitability were relatively the most important dimensions, followed by leverage and liquidity. Furthermore, results revealed the relative importance of the indicators from the most to the least important. Results also revealed the effect of COVID-19 on energy companies’ financial performance, demonstrating the change over the three years. Implications include providing insights for energy companies on the financial dimensions and indicators to be maintained and monitored in the case of pandemics. Furthermore, to assist decision-makers in the energy sector in developing strategies to mitigate financial performance disparities during and post-pandemics.

Tourism is an upcoming industry with a high potential for future growth. Many factors influencing destination image (DI) are affecting tourism development. Therefore, studying factors influencing DI is essential. This research study aims to model the factors influencing DI in the tourism industry. A total of 15 factors were the focus of the study. Data on the factors were collected from 10 tourism industry experts. An integrated modeling approach was adopted using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modelling (ISM). Interrelationships between the factors, causal effects, relative importance weights, ranks, and driving and dependence powers were analyzed to develop causal and interpretive structures. The developed model revealed that political stability is foundational to other aspects of DI. Then, factors related to safety and security, policy rules and regulations, tourism infrastructure, information and communication technologies, environment, economic development and affluence, fairs, exhibits, and festivals in a destination should be considered. These affect others related to health and hygiene, transport infrastructure, natural and cultural resources, human resources, quality of services, prices, hospitality, friendliness, and receptiveness aspects in a destination. The developed model provides a valuable framework for decision-makers in the tourism industry to enhance and shape the DI.