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Abstract
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Kraus, J., Scholz, D., & Baumann, M. (2021). What's Driving Me? Exploration and Validation of a Hierarchical Personality Model for Trust in Automated Driving. Human Factors, 63(6), 1076-1105. https://doi.org/10.1177/0018720820922653
The incorrect version of the above article was published in the issue and has now been replaced with the correct version.
Abstract for corrected version:
Objective
This paper presents a comprehensive investigation of personality traits related to trust in automated vehicles. A hierarchical personality model based on Mowen's (2000) 3M model is explored in a first and replicated in a second study.
Background
Trust in automation is established in a complex psychological process involving user-, system- and situation-related variables. In this process, personality traits have been viewed as an important source of variance.
Method
Dispositional variables on three levels were included in an exploratory, hierarchical personality model (full model) of dynamic learned trust in automation, which was refined on the basis of structural equation modeling carried out in Study 1 (final model). Study 2 replicated the final model in an independent sample.
Results
In both studies, the personality model showed a good fit and explained a large proportion of variance in trust in automation. The combined evidence supports the role of extraversion, neuroticism, and self-esteem at the elemental level; affinity for technology and dispositional interpersonal trust at the situational level; and propensity to trust in automation and a priori acceptability of automated driving at the surface level in the prediction of trust in automation.
Conclusion
Findings confirm that personality plays a substantial role in trust formation and provide evidence of the involvement of user dispositions not previously investigated in relation to trust in automation: self-esteem, dispositional interpersonal trust, and affinity for technology.
Application
Implications for personalization of information campaigns, driver training, and user interfaces for trust calibration in automated driving are discussed.
Language: en |