Rethinking Conversation Styles of Chatbots from the Customer Perspective: Relationships between Conversation Styles of Chatbots, Chatbot Acceptance, and Perceived Tie Strength and Perceived Risk

Abstract

Grounded in the Stereotype Content Model, Risk Perception Theory, Technology Acceptance Model, and Relational Embeddedness Theory, this research delves into the relationship between chatbot conversation styles, customer risk, and the mediating role of chatbot acceptance and tie strength in online shopping. A 2 (warm vs. cold) * 2 (competent vs. incompetent) between-subjects experiment is conducted on 320 participants and the results obtained from two-way ANOVA and PROCESS macro revealed that: (a) customer-perceived risk decreases with conversation warmth rather than conversation competence; (b) customer acceptance of chatbots improves with conversation competence rather than conversation warmth, while not acting as an intermediary factor between the conversation styles and customer-perceived risk; (c) customer perceived tie strength increases with both conversation warmth and conversation competence. The findings contribute to the existing literature about the impact of chatbot anthropomorphism on customer cognitive processes and offer executives insights into the design of customer-friendly chatbots.