Abstract
Smart city technologies such as transportation and parking systems make our daily lives more efficient and intelligent. However, it is impossible to implement a smart mobility system without analyzing the individual's behavior toward the new technology. This research study attempts to develop a framework for predicting smart mobility antecedents using SEM in primary data analysis. The Technology Acceptance Model (TAM) was the conceptual foundation for this study. To achieve the objectives of the study, one thousand five hundred and twelve effective questionnaires were collected and analyzed using Smart PLS 3.3. The results show that perceived usefulness, perceived ease of use, and perceived risk significantly affect attitudes towards adopting smart mobility systems. Our study provides a comprehensive framework to understand individual-level smart city technology adoption. This study offers implications for policymakers to update existing policies concerning road technology.
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