Covid-19 Media Coverage and Stock Return

Obeidat, Ghassan; Almasarwah, Adel; Almaharmeh, Mohammad; Ata, Barış

doi:10.15379/ijmst.v10i2.1255

Cited by 1 publication

(2 citation statements)

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“…A study was undertaken in India by scholars Acharjya and others [14] to investigate the moderating effect of gender and age on e-learning during the COVID-19 epidemic. The researcher expanded the UTAUT model by including components related to computer anxiety, technological anxiety, and attitude.…”

Section: Past Researchmentioning

confidence: 99%

“…The proposed model in Figure 3.1 will determine the relationship between the selected constructs; For this study, the behavioral intention construct is selected as a dependent variable to determine student intent to use elearning through COVID-19 in Pakistan. This construct is extensively selected by many Investigators to find the behavior intention of users [13,14,15,16].…”

Section: Predictors and Hypothesis Synthesismentioning

confidence: 99%

See 1 more Smart Citation

Moderating Effect of Covid-19 On E-Learning Predictors: An Empirical Study on Student's Perspective in Sindh, Pakistan

Keerio,

Shah,

Luhana

et al. 2023

ijmst

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During the COVID-19 pandemic, e-learning has been crucial for maintaining educational continuity while adhering to safety protocols and using social distancing guidelines. The worldwide spread of the pandemic has significantly disrupted traditional face-to-face educational practices, compelling the rapid and extensive adoption of electronic learning alternatives. As a result, it is crucial to understand the key factors influencing e-learning adoption in developing countries such as Pakistan during COVID-19. This research aims to analyze the moderating role of COVID-19 on key e-learning predictors using the UTAUT model by including some external Constructs. This study employed a qualitative survey-based methodology, with a sample size of 460 responses from students who engaged in e-learning during the period of the COVID-19 pandemic. The PLS-SEM technique was employed for data analysis utilizing the SmartPls4 version 4.0.9.2 program. A Model was formed based on the UTAUT model by including some external variables. Empirical results revealed that during COVID-19 the most important factors predicting student behavior intention for e-learning adoption were, Computer anxiety, System characteristics, Facilitating conditions, Social influence, and COVID-19 itself. Furthermore, results also demonstrate that there was a sizable amount of COVID-19 moderating effect (0.022) on the association between social Influence and Behavior intention which somehow weakened the adoption of e-learning during COVID-19 time. The R-square value of the model is (0.677), which indicates that the model possesses substantial explanatory power, and the Q-square value is (0.662) indicating the establishment of Model predictive relevance.

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Section: Past Researchmentioning

confidence: 99%