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There are several reasons why the fear of vaccination has caused populationrejection. Questions have been raised by students regarding the effectivenessof vaccines, which in turn has led to vaccination hesitancy. Studentsperceptions are influenced by vaccination hesitancy, which affects theacceptance of e-learning platforms. Hence, this research aimed to examine thepost-acceptance of e-learning platforms on the basis of a conceptual model thatemploys different variables. Distinct contribution is made by every variable tothe post-acceptance of e-learning platforms. A hybrid model was used in thecurrent study in which technology acceptance model (TAM) determinants wereemployed along with other external factors such as fear of vaccination,perceived routine use, perceived enjoyment, perceived critical mass, andself-efficiency which are directly linked to post-acceptance of e-learningplatforms. The focus of earlier studies on this topic has been on thesignificance of e-learning acceptance in various environments and countries.However, in this study, the newly-spread use of e-learning platforms in thegulf area was examined using a hybrid conceptual model. The empirical studiescarried out in the past mainly used structural equation modelling (SEM)analysis; however, this study used an evolving hybrid analysis approach, inwhich SEM and the artificial neural network (ANN) that are based on deeplearning were employed. The importance-performance map analysis (IPMA) was alsoused in this study to determine the significance and performance of eachfactor. The proposed model is backed by the findings of data analysis.

The empirical study of e-learning post-acceptance after the spread of COVID-19: A multi-analytical approach based hybrid SEM-ANN