The COVID-19 Pandemic has led to social isolation; however, with the help of technology, education can continue through this tough time. Therefore, this research attempts to explore the Unified Theory of Acceptance and Use of Technology (UTAUT) through the expansion of the model. Also, make it relevant to investigate the influence of social isolation, and the moderating role of Corona fear on Behavioral Intention of the Learning Management System and its Use Behavior of Learning Management System among students. The data was analyzed using Partial Least Square (PLS) and Structural Equation Modelling (SEM). The findings show a positive link of Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Social Isolation on Behavioral Intention of LMS and, also between Behavioral Intention of LMS and its Use behavior. Moreover, the results of the moderation analysis show that Corona fears only moderates the link of Performance Expectancy and Social influence with Behavioral Intention of LMS. The findings imply the need for improving the LMS experience to increase its Behavioral Intention among students. Finally, the author's recommendation for future researchers is to examine the extended model in other countries and territories to analyze Coronavirus's influence on e-learning acceptance.

When employees do work by "going beyond" or by "giving their all." They look at their job as more than just a paycheck and eager to do all they can to make their work environment more effective, though such actions are not associated with their job descriptions. Such behaviors are sometimes because of the personality of an individual, but sometimes organizations boost such behaviors by providing a peaceful

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Ride-sharing services are a sustainable form of the transportation system that needs to be popularized among students by examining the crucial factors that determine the students’ behavior to use the innovative service. Therefore, this paper attempts to explore students’ behavior regarding the use of ride-sharing services by extending the “Technology Acceptance Model.” The expanded model includes the current TAM structures and integrates contextual stimuli that may or may not affect the ride-sharing service’s behavior. Moreover, the study focuses on determining the moderating role of perceived risk between the proposed relationships. The paper uses PLS-SEM to analyze the research model and determine the results of the hypotheses. The findings of this research are useful for ride-sharing service providers and policymakers who can promote the services among students by reducing the perceived risks and promoting the environmental benefits of ride-sharing. Furthermore, the limitations of this paper pose future research directions.

E-Learning has been an exceptional support for learners across the globe. Many people are using electronic media for different purposes. Hence, learners, especially students, can benefit from the electronic system as well. Therefore, the purpose of this study is to examine the adoption level of e-learning systems by using the extended model of UTAUT2. The data was collected using the survey method, and for this purpose, the five-point Likert scale has been used. The statistical techniques applied to the data set were confirmatory factor analysis and partial least square structural equation modeling. The results reveal that performance expectancy, effort expectancy, social influence, facilitating conditions, habit, knowledge acquisition, and knowledge sharing are positively linked with behavioral intention to use e-learning systems except for hedonic motivation. The modified model adds two new predictors: knowledge acquisition and knowledge sharing that influence students' acceptance of e-learning systems. Therefore, it will provide the educationists and policymakers a new insight into whether students are willing to adopt the E-learning system for daily use. Keywords: E-Learning System, Behavioral intention, Knowledge acquisition, Knowledge sharing, Higher education, PLS-SEM