Unveiling determinants of autonomous vehicle adoption through SEM-ANFIS modelling

This study aims to examine the factors influencing individuals’ intentions to use ‘autonomous vehicles’ (AVs). By extending the ‘Technology Acceptance Model (TAM)’ with variables such as security risk, privacy concerns, perceived compatibility, personal innovativeness, and social influence, the research seeks to provide insights into the drivers and barriers to AV adoption. Data were collected from 378 drivers in Vietnam using social media platforms. A mixed-method approach was employed, combining ‘Structural Equation Modelling (SEM)’ to test direct and moderating effects, and ‘Adaptive Neuro-Fuzzy Inference Systems (ANFIS)’ to evaluate the relative importance of predictive variables in shaping the intention to use AVs. The findings reveal that perceived ease of use, perceived usefulness, privacy concerns, perceived compatibility, personal innovativeness, and social influence significantly drive users’ intentions to adopt AVs. Security risks and privacy concerns were found to act as moderating factors. ANFIS analysis highlighted personal innovativeness, perceived compatibility, perceived usefulness, and attitude as the most influential predictors of perceived usefulness, perceived ease of use, attitude, and intention to use AVs, respectively. The findings can guide policymakers and stakeholders in designing effective strategies and policies to facilitate the implementation of AVs in emerging markets.