A Hybrid Three-staged SF-AHP, PLS-SEM and ANN Model to Predict Vaccination Intention against COVID-19 Pandemic
Description
Spherical Fuzzy Analytic Hierarchy Process (SF-AHP), Structural Equation Model (SEM), and Artificial Neural Network (ANN) approaches were applied to test the proposed hypotheses and predict the vaccination intention
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Steps to reproduce
The proposed research framework consists of 3 phases. In Phase 1, assigning fuzzy weights to criteria based on pairwise comparisons is done using the SF-AHP model. In Phase 2, the PLS-SEM approach is used to validate the hypotheses as indirect/direct effects. In Phase 3, significant predictors from PLS-SEM analysis were taken as the ANN model’s input neurons. According to the normalized importance obtained from the multilayer perceptrons of the feed-forward-back-propagation ANN algorithm, we can find significant effects of vaccination intention and determine the accurate prediction rates.