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Two Routes to Trust Calibration: Effects of Reliability and Brand Information on Trust in Automation
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Author(s): Johannes Maria Kraus (Ulm University, Ulm, Germany), Yannick Forster (BMW Group, Bayern, Germany), Sebastian Hergeth (BMW Group, Bayern, Germany)and Martin Baumann (Ulm University, Ulm, Germany)
Copyright: 2022
Pages: 20
Source title:
Research Anthology on Cross-Disciplinary Designs and Applications of Automation
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-3694-3.ch045
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Abstract
Trust calibration takes place prior to and during system interaction along the available information. In an online study N = 519 participants were introduced to a conditionally automated driving (CAD) system and received different a priori information about the automation's reliability (low vs high) and brand of the CAD system (below average vs average vs above average reputation). Trust was measured three times during the study. Additionally, need for cognition (NFC) and other personality traits were assessed. Both heuristic brand information and reliability information influenced trust in automation. In line with the Elaboration Likelihood Model (ELM), participants with high NFC relied on the reliability information more than those with lower NFC. In terms of personality traits, materialism, the regulatory focus and the perfect automation scheme predicted trust in automation. These findings show that a priori information can influence a driver's trust in CAD and that such information is interpreted individually.
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