Chatbot Schema Activation: When Anthropomorphic Language Leverages Word-of-Mouth

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Abstract
This study investigates how anthropomorphic language and chatbot schema (a customer’s cognitive framework for understanding and interacting with a chatbot) jointly influence customer electronic word-of-mouth (eWOM). Across two experiments, we examine how anthropomorphic language (such as empathetic language and emojis) impacts customers’ engagement with chatbots. Study 1 provides directional evidence suggesting that anthropomorphic language is associated with greater eWOM when a chatbot schema was active, but not when it is inactive. Study 2 demonstrates that the effects of anthropomorphic language on authenticity and eWOM are contingent on the chatbot’s competence. Together, these findings suggest that linguistic cues may improve chatbot interactions, beyond their visual appearance. This research has implications for marketing practitioners, helping them to formulate effective strategies based on chatbot disclosure and competence.

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