Individuals are often biased in their judgments about AI, especially when it comes to customer-support-oriented service interactions. With three preregistered experiments (and three supplementary studies), the current research examines how marketplace status creates systematic differences in customer biases against chatbot-delivered services, and what firms can do to mitigate the impact of those biases on their evaluations. In Study 1 (N = 1,019), the authors show that high-tier (vs. basic) customers react more negatively to chatbot-delivered services, even when the objective service delivered is the same. They also demonstrate that greater perceptions of uniqueness neglect and entitlement among high-tier (vs. basic-tier) customers are possible explanations for this tier-based bias against chatbots. Study 2 (N = 1,196) demonstrates the effectiveness of three “framing interventions” that significantly reduced high-tier customers’ bias against chatbots. Finally, Study 3 (N = 899) examines different ways of acquiring a high marketplace status—earned versus unearned—as a boundary condition for the main effect, while experimentally demonstrating the mediational role of entitlement in addition to uniqueness neglect. Together, this research advances the understanding of human–robot interactions from a marketplace status lens and provides concrete managerial strategies for communicating about automated customer support services.
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