Competence (human resources)

Perspective (graphical)

World Wide Web

Artificial intelligence

Psychology

Chatbot

Computer science

Social psychology

Information Processing & Management

Text-based chatbots are being touted as a disruptive innovation with unprecedented business potential. However, frequent failures in human–chatbot conversations have led to consumer pushback. This study investigates the response of consumers to chatbots in terms of their intention to switch to human agents. Drawing upon the stimulus–organism–response (SOR) framework, focus is placed on how the anthropomorphic attributes of chatbots influence consumers’ perceived trust in chatbots and its implications for switching intention. Further, the moderating role of relationship norms in the relationships between the anthropomorphic attributes and trust in chatbots is examined. A mixed-methods approach is used; the qualitative analysis reveals three main anthropomorphic attributes of chatbots, two types of relationship norms and the specific response to chatbots. The quantitative results suggest that the anthropomorphic attributes of perceived warmth and perceived competence positively affect consumers’ perceived trust in chatbots, whereas communication delay negatively affects it. Relationship norms are found to moderate some of these effects such that exchange relationships strengthen the importance of perceived competence on trust, although communal relationships do not moderate the effects of perceived warmth on trust. Trust in chatbots negatively affects consumers’ intention to switch to a human agent. Theoretical and managerial implications are also discussed for scholars and practitioners in ways to improve the design and maximize the utility of chatbots.

Human vs. AI: Understanding the impact of anthropomorphism on consumer response to chatbots from the perspective of trust and relationship norms