Overcoming Awkward Moments: The Role of Robot Interaction Modality in Shaping Service Robot Acceptance
(A2025-124841)

AUTHORS

Jooyoung Park, Peking University HSBC Business School; Julia Talagrand, Peking University HSBC Business School; Feng Pan, Peking University HSBC Business School; Keongtae Kim, Chinese University of Hong Kong

ABSTRACT

This study examines how robot interaction modality—voice versus text—affects robot acceptance during embarrassing service encounters. We propose that users interacting with text-enabled robots will show greater acceptance than those using voice-enabled robots in high-embarrassment situations. We also hypothesize that perceived control moderates this relationship, impacting how embarrassment and interaction modality influence users’ acceptance of service robots. Our findings from two studies support these hypotheses: Study 1 demonstrates that consumers are more likely to accept text-enabled robots when experiencing higher embarrassment, while Study 2 reveals that perceived control mediates the interaction between embarrassment and robot modality in a retail context. These results enhance theoretical understanding of embarrassment and robot design and offer practical implications for healthcare and retail sectors by highlighting the need to improve users’ perceived control during robot interactions. We suggest future research directions to investigate factors like voice gender and varying degrees of embarrassment to further deepen insights into consumer acceptance of technology.