Gender Stereotyping in Robot Service Failures

Abstract

AI agents, such as service robots, could encompass gender cues. However, little is known regarding whether and how customers apply gender stereotyping to service failures in gendered service tasks performed by robots. Drawing on gender stereotype theory, we investigate the joint effects of robot gender (feminine vs. masculine) and task type (female-dominated vs. male-dominated) on customer dissatisfaction following service failures. Study 1 reveals that feminine service robots are perceived as more communal but as equally agentic as their masculine counterparts. Study 2 demonstrates that feminine (vs. masculine) service robots generate lower customer dissatisfaction when failing a female-dominated task. However, this discrepancy diminishes when failures occur in a male-dominated task. Perceived communion and tolerance serially mediate such robot gender effects. Our findings suggest that using feminine robots across all service categories may be a cost-effective strategy for hospitality organizations, eliminating the need to vary robot gender by task type.