Determinants of smart government continuous use: A two-staged structural equation modeling-artificial neural network approach

This study aimed to develop and empirically validate an integrated model for continuous smart government service usage. This model integrates constructs from the unified theory of acceptance and use of the technology framework with the expectation-confirmation model, along with an additional construct: trust. Structural equation modeling (SEM) was used to analyze data collected via online questionnaires from 369 people who utilized smart government services in the United Arab Emirates. Next, an artificial neural networks model was used to rank the relative influence of the significant predictors identified through SEM analysis. The findings reveal that, among the significant predictors affecting the continuous use of smart government services, facilitating conditions, satisfaction, and perceived usefulness had the most substantial impact. Furthermore, this study highlights the direct influence of perceived usefulness, confirmation, facilitating conditions, effort expectancy, social influence, and public trust on citizen satisfaction.