Chatbot vs. Human: The Impact of Responsive Conversational Features on Users’ Responses to Chat Advisors

Abstract

As educational organizations increasingly consider supporting or replacing human chat advisors with chatbots, it is crucial to examine if users perceive a chatbot differently from a human. Chatbots’ conversational features may signal responsiveness and thus improve user responses. To explore this, we conducted three online experiments using a study advising setting. We computed pooled data analyses because the individual study results did not provide clear support for our hypotheses. Results indicate that users prefer human agents regarding competence and intention to use but not perceived enjoyment. Responsiveness increased likability, warmth, and satisfaction. Perceptions of the interaction mediated the responsiveness effects. Our findings suggest that educational organizations can support their study advising departments with well-functioning chatbots without eliciting negative user responses.

Keywords

• agent type
• responsiveness
• chatbot
• user response
• human-machine communication