Customer–Robot Interaction Beyond the First Encounter: A Reciprocal Framework and Quadrant Model for Value Co-Creation

Abstract

As service robots move from factory floors to frontline service encounters, their success increasingly depends on the quality of customer-robot interaction (CRI). Existing studies, however, remain fragmented and predominantly grounded in linear technology adoption models, offering limited insight into the dynamic and reciprocal nature of CRI over time. Addressing this gap, this systematic literature review synthesises 113 peer-reviewed articles and makes two main contributions. First, it develops a reciprocal framework that conceptualises CRI as path-dependent process in which drivers and barriers shape experiential responses, leading to attitudinal and behavioural outcomes that, in turn, recalibrate customer expectations through feedback loops. This framework advances prior one-way technology adoption models (e.g., TAM/UTAUT) by focusing on the value creation through repeated interactions in robotic service encounters. Second, the review introduces a quadrant-based model of robot-task fit structured by task complexity and service goal orientations. Extending existing robot typologies, this model specifies when particular experiential mechanism dominate and how reciprocal feedback loops vary across four robot roles: mechanical, analytical, socially interactive, and empathetic. Together, these contributions offer a holistic and contingent understanding of CRI, generating actionable insights for future research developments and for the design of effective, human-centric service robots.