- Khadija Alhumaid
Research & Innovation Division, Rabdan Academy, Abu Dhabi, UAE
kalhumaid@ra.ac.ae
5G Adoption Modeling in the Gulf: A Deep Learning–Driven SEM Framework for Intelligent and Dependable Wireless Networks
The research aims to adopt 5G services in Gulf countries with an SEM-ANN approach. 5G services are gauged with a modified Technology Acceptance Model (TAM) with Perceived Skill Readiness and Perceived Resources constructions to comprehend infrastructure and user competence. Four hundred eighty-five participants (January-February 2022) were examined in the PLS-SEM approach to validate the measurement and structural relationships (R² for behavioral intention = 0.476). A trained two-hidden-layer multilayer perceptron ANN was used after PLS-SEM to account for nonlinear relations and increase predictive accuracy (ANN R² ≈ 0.80). IPMA and sensitivity ranking show that the most important aspects of 5G adoption are Perceived Enjoyment and Perceived Resources. This work conceptually expands the TAM with Infrastructure and Skill Readiness and Methodologically with SEM-ANN hybrid and IPMA metrics. Focus on user-centered experience design and infrastructure readiness are the derived recommendations for management to increase the 5G network reliability. Future research directions are discussed.