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Title
Japanese: 
English:Effect of different listening behaviors of social robots on perceived trust in human-robot interactions 
Author
Japanese: ANZABI Naeimeh, 梅室 博行.  
English: Naeimeh Anzabi, Hiroyuki Umemuro.  
Language English 
Journal/Book name
Japanese: 
English:International Journal of Social Robotics 
Volume, Number, Page Vol. 15        pp. 931–951
Published date Apr. 24, 2023 
Publisher
Japanese: 
English:Springer 
Conference name
Japanese: 
English: 
Conference site
Japanese: 
English: 
DOI https://doi.org/10.1007/s12369-023-01008-x
Abstract With the increased use of social robots in prominence and beyond functional performance, they are expected to foster trust and confidence in people. Various factors involve providing social robots with more trustworthy behavior. This study investigated whether the listening behavior of a robot can affect the perception of being trustworthy in human–robot interaction. Therefore, we designed four different listening behaviors, including non-active listening, active listening, active empathic listening, and verbal empathic listening, for a social robot and evaluated the impact of each behavior on the participants’ likelihood of trusting the robot, using a between-subject design. Participants in the four groups followed a conversation with a robot that simulated one of the listening behaviors, and their general trust toward the robot as well as affective and cognitive trust was measured. The results indicated that active empathic listening behavior provided the participants with the highest impression of trustworthiness compared to non-active and active listening behavior in all three dimensions, including general trust, affective trust, and cognitive trust. Furthermore, a robot with active listening behavior was evaluated to be more trustworthy than a non-active listening robot. For verbal and non-verbal dimensions of listening behavior, it was confirmed that non-verbal behaviors such as nodding, body movement, and eye gaze in addition to verbal behaviors had a significant effect in eliciting higher trust in human-robot interaction, in both general and affective trust. However, no significant differences were found in cognitive trust. Considering the results, we conclude that designing social robots with active (empathic) listening behavior can improve trust perception in human-robot interaction in different fields such as education, healthcare, and business.

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