Factors influencing behavioral intentions to use conditionally automated vehicles

Sjaan Koppel · David B. Logan · Xin Zou · Fareed Kaviani · Hayley McDonald · Joseph F. Hair +3 more

12 citations0/0 files storedJournal of Safety Research

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Technology Adoption and User Behaviour Human-Automation Interaction and Safety Transportation and Mobility Innovations

Abstract

• Conditionally automated vehicles will be integrated into the road system soon. • Current study explored factors influencing intentions to use conditionally automated vehicles. • Perceived usefulness strongly impacts intentions to use conditionally automated vehicles. • Education programs are key to helping consumers understand conditionally automated vehicles' capabilities and limits. Background: This study explored factors influencing the acceptance of conditionally automated vehicles among Australian drivers by extending the Technology Acceptance Model with the Technology Readiness Index. Method: Data from an online survey of 844 participants were analyzed using partial least squares structural equation modeling (PLS-SEM). Results: Perceived usefulness had the strongest direct effect on behavioral intention (0.469, p < 0.001), followed by attitude (0.318, p < 0.001). Innovativeness positively influenced behavioral intention (0.183, p < 0.001), while insecurity had a negative impact (−0.071, p < 0.01). Optimism and discomfort were not significant. Perceived usefulness also had significant indirect effects through attitude (0.156, p < 0.001) and trust (0.072, p < 0.001). Perceived ease of use indirectly influenced behavioral intention through perceived usefulness (0.306, p < 0.001), attitude (0.102, p < 0.001), trust (0.047, p < 0.001), and their combinations. Trust indirectly affected behavioral intention via attitude (0.130, p < 0.001). Perceived security and privacy risks had indirect negative effects through trust and attitude (−0.035, p < 0.001; −0.005, p < 0.05). Conclusion: These results suggest that fostering acceptance among less tech-savvy individuals may help promote positive attitudes, increase conditionally automated vehicle adoption, and potentially enhance road safety. Practical implications: These findings suggest a need for targeted programs to enhance perceived usefulness and trust while addressing security and privacy concerns, ultimately contributing to safer road systems through the adoption of conditionally automated vehicles.

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References

1989Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology 2018When to use and how to report the results of PLS-SEM 2000A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies 2021Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R 2019Assessing measurement model quality in PLS-SEM using confirmatory composite analysis 2014An Updated and Streamlined Technology Readiness Index 2015Investigating the Importance of Trust on Adopting an Autonomous Vehicle 2018The roles of initial trust and perceived risk in public’s acceptance of automated vehicles

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