An integrated autonomous vehicles acceptance model: Theoretical development and results based on the UTAUT2 model

• The study extends UTAUT2 with perceived risk, trust in technology, perceived safety, innovativeness and price sensitivity. • Trust in technology is the most important predictor of intention to use autonomous vehicles. • Price sensitivity is a better predictor than price value for autonomous vehicle acceptance. • Perceived risk and effort expectancy are not significantly related to the intention to use autonomous vehicles in the UAE. Several studies have examined acceptance of autonomous vehicles (AVs) by applying the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model and extending it with factors applicable to AV acceptance. However, this has resulted in a multitude of factors with mixed findings about their impact. This study develops and validates an integrated UTAUT2 model for AV acceptance by conducting a systematic quantitative review of the AV studies that have extended the UTAUT2 model. From the initially identified 298 studies, 28 met the eligibility criteria and were analyzed to identify the most studied external factors, which the results revealed as perceived risk, perceived safety, trust in technology, innovativeness, and price sensitivity. An integrated UTAUT2 model including these factors was proposed and then validated by collecting and analyzing data from 402 respondents. The partial least squares-structural equation modeling (PLS-SEM) results showed that trust in technology was the most influential predictor of AV acceptance, followed by innovativeness, performance expectancy, perceived safety, hedonic motivation, social influence, and price sensitivity. Evidence was not found to support the impact of perceived risk, effort expectancy, and price value on AV acceptance. This integrated model offers a foundation for further AV acceptance research. The study also provides a more nuanced understanding about the factors influencing AV acceptance to guide policy makers and practitioners in devising effective AV adoption strategies.