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The Effects of Chatbot Anthropomorphism and Self-disclosure on Mobile Fashion Consumers' Intention to Use Chatbot Services

  • Kim, Minji (Business Administration Program, Angelo State University) ;
  • Park, Jiyeon (Dept. of Fashion Design & Textiles, Inha University) ;
  • Lee, MiYoung (Dept. of Fashion Design & Textiles, Inha University)
  • Received : 2021.11.25
  • Accepted : 2021.12.26
  • Published : 2021.12.30

Abstract

This study investigated the effects of the chatbot's level of anthropomorphism - closeness to the human form - and its self-disclosure - delivery of emotional exchange with the chatbot through its facial expressions and chatting message on the user's intention to accept the service. A 2 (anthropomorphism: High vs. Low) × 2 (self-disclosure through facial expressions: High vs. Low) × 2 (self-disclosure through conversation: High vs. Low) between-subject factorial design was employed for this study. An online survey was conducted and a total of 234 questionnaires were used in the analysis. The results showed that consumers used chatbot service more when emotions were disclosed through facial expressions, than when it disclosed fewer facial expressions. There was statistically significant interaction effect, indicating the relationship between chatbot's self-disclosure through facial expression and the consumers' intention to use chatbot service differs depending on the extent of anthropomorphism. In the case of "robot chatbots" with low anthropomorphism levels, there was no difference in intention to use chatbot service depending on the level of self-disclosure through facial expression. When the "human-like chatbot" with high anthropomorphism levels discloses itself more through facial expressions, consumer's intention to use the chatbot service increased much more than when the human-like chatbot disclosed fewer facial expressions. The findings suggest that chatbots' self-disclosure plays an important role in the formation of consumer perception.

Keywords

Acknowledgement

This work was supported by INHA UNIVERSITY Research Grant (2019).

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