Testing a structural model of young driver willingness to uptake Smartphone Driver Support Systems

Area of Science:

• Road safety
• Human-computer interaction
• Psychology

Background:

• Growing interest in smartphone applications for monitoring driver behavior (SDSSs) to reduce risky driving in young people.
• Willingness to use SDSSs is crucial for realizing their potential in mitigating risky driving behaviors.
• Existing research in driver monitoring and Technology Acceptance (TA) provides a foundation for understanding user adoption.

Purpose of the Study:

• To test a novel structural model of willingness to use SDSSs among young drivers.
• To investigate the influence of perceived risks, gains, usability, and social factors on the adoption of SDSSs.
• To identify key determinants of behavioral intention (BI) to use SDSSs in a young driving population.

Main Methods:

• A study involving 333 smartphone users aged 18-24 with full Irish driving licenses.
• Online questionnaire assessing willingness to use SDSSs, incorporating perceived risks, gains, usability, and social influences.
• Exploratory and confirmatory factor analyses followed by structural equation modeling (SEM).

Main Results:

• Perceived gains and social influence had significant direct effects on behavioral intention (BI) to use SDSSs.
• Perceived risks and social influence indirectly affected BI, mediated by perceived gains.
• The proposed model explained 72.5% of the variance in willingness to adopt SDSSs.
• Model effects were consistent across gender, risk levels, and technology adoption propensity.

Conclusions:

• Perceived gains and social influences are key drivers of young drivers' willingness to use SDSSs.
• Understanding these factors can inform the development of effective behavioral change interventions to increase SDSS adoption.
• The findings suggest a robust model applicable across diverse young driver demographics.