信任校准的两条路径:可靠性和品牌信息对自动化信任的影响

IF 0.2 Q4 COMPUTER SCIENCE, CYBERNETICS International Journal of Mobile Human Computer Interaction Pub Date : 2019-07-01 DOI:10.4018/IJMHCI.2019070101
J. Kraus, Yannick Forster, Sebastian Hergeth, M. Baumann
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引用次数: 19

摘要

信任校准在系统交互之前和过程中根据可用信息进行。在一项在线研究中,N = 519名参与者被介绍给一个有条件自动驾驶(CAD)系统,并收到关于自动化可靠性(低与高)和CAD系统品牌(低于平均水平、平均水平与高于平均水平的声誉)的不同先验信息。在研究过程中,对信任度进行了三次测量。此外,对认知需求(NFC)和其他人格特征进行了评估。启发式品牌信息和可靠性信息对自动化信任都有影响。在精化似然模型(ELM)中,高NFC的参与者比低NFC的参与者更依赖可靠性信息。在人格特征方面,物质主义、监管焦点和完美的自动化方案预测了自动化信任。这些发现表明,先验信息可以影响驾驶员对CAD的信任,并且这些信息是单独解释的。
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Two Routes to Trust Calibration: Effects of Reliability and Brand Information on Trust in Automation
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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CiteScore
4.70
自引率
0.00%
发文量
5
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