聊天机器人
互动性
叙述的
心理学
计算机科学
期望理论
人机交互
万维网
社会心理学
语言学
哲学
作者
Yuan Sun,Jin Chen,S. Shyam Sundar
标识
DOI:10.1016/j.jbusres.2023.114403
摘要
Powered by artificial intelligence (AI), chatbots are increasingly capable of simulating human-like conversations. But, is this desirable for strategic communications? Will chatbots be more persuasive if they are more human-like, not only in their appearance but also in their interaction and delivery of advertising content? We explored these questions with a 2 (chatbot profile: human-like vs. machine-like) x 2 (message interactivity: high vs. low) x 2 (ad type: narrative vs. factual) experiment (N = 414). Data reveal that high message interactivity fosters positive attitudes toward the chatbot and the ad by mitigating violated expectancy. Narrative ads promote chatbot advertising through perceived transportation. A three-way interaction revealed that when a chatbot is machine-like in appearance, higher interactivity and adoption of a narrative style of delivery serve to increase ad persuasiveness by heightening social presence. Theoretical and practical implications for chatbot advertising are discussed.
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