An appropriate human-computer trust (HCT) is a key element affecting the use of Intelligent Decision Aids (IDA). Through item-level analysis, exploratory factor analysis, and confirmatory factor analysis, this study showed that the revised version of the HCT consisting of two sub-factors cognitive-based trust (10 items) and affect-based trust (6 items) was a valid and reliable scale to assess human’s trust towards computers in China, using two groups of samples with different occupation backgrounds in China. Moreover, variables trust in automation and interpersonal trust were used to examine HCT’s criterion validity, both of which showed moderate to high significant correlations with each dimension of HCT. It was the first psychometric assessment and validity test of the HCT scale in different culture using a large-scale dataset and expected to provide both theoretical and practical values for future researchers.

This study explores the relationship between the perceived intelligence of robots and individuals’ willingness to use them, focusing on the mediating role of trust and the moderating role of self-efficacy. A total of 462 Chinese adults participated in the study. They completed four assessments: the Godspeed Questionnaire (GQS), the Willingness to Integrate Service Robots Scale (WISRS), the Social Service Robot Interaction Trust (SSRIT) Scale, and the Self-Efficacy in Human-Robot Interaction Scale (SE-HRI). Results revealed that perceived intelligence positively predicts willingness to use robots. Trust was found to mediate the relationship. Moreover, self-efficacy moderated both the direct association between perceived intelligence and willingness to use robots, as well as the indirect mediating effect of trust. The findings offer provided novel insights to understand the mechanism of willingness to adopt robots.

Research on consumers’ trust toward interaction with Artificially Intelligent (AI) social robots in service delivery has gained much more interest due to the outbreak of COVID-19 pandemic. However, this topic has not been widely invesgiated in China. To provide a psychometrically sound instrument in diverse cultural contexts, this study was to validate a scale of Social Service Robot Interaction Trust (SSRIT) that measures consumers’ trust toward interaction with AI social robots in service delivery in a Chinese sample of adults. The results showed that the Chinese version of the SSRIT was validated with reliability and validity, suggesting that the Chinese version of the SSRIT could be used as an effective tool to assess trust in AI social robots in service delivery within the Chinese context. The implications of the findings were also discussed.

With increasing use of robots in social life, individuals need to interact with robots more frequently, and user-anxiety about robots has attracted an extensive research attention. However, this topic has not been explored as much in China. To provide a scale for research on robot anxiety in China, this study translated and examined the reliability and validity of the Robot Anxiety Scale (RAS). The results showed that the Chinese version of RAS had an acceptable content validity. The exploratory factor analysis (EFA) showed that only one factor was extracted in this study, and the confirmatory factor analysis (CFA) verified the factor structure, with the model-fitting index reaching an acceptable standard: χ2/df = 3.26, SRMR = .02, CFI = .99, GFI = .96, TLI = .98, RMSEA = .06. These findings were cross validated using Rasch measurement, in addition to further investigation of other RAS psychometric properties under the Rasch framework. Moreover, criterion validity analysis results also showed that robot anxiety was significantly positively correlated with state anxiety, trait anxiety, and negative emotions, while robot anxiety was significantly negatively correlated with trust in automation and positive emotions. In conclusion, the Chinese version of RAS is an effective tool for measuring robot anxiety in China.