Automated, human, or semi-automated service in restaurants? An investigation of technology-enabled service designs and customer attribution

Abstract

Self-serving bias tends to lead customers to attribute ideal outcomes to themselves while blaming external factors for non-ideal outcomes. This attribution process complicates the current service configuration owing to service increasingly incorporating automated or semi-automated processes where the traditional human services are replaced or reduced. This research provides insights into how such changing service dynamics may impact restaurant customers' attribution behavior. By utilizing a 2 × 3 between-subject scenario-based experimental design, this study shows that restaurant service types (automated, employee, and semi-automated services) and service outcomes (with and without service failure) influence consumer attribution and subsequent service satisfaction. This study allows a better understanding of how customers perceive a service failure and the absence of service failure when such services interface with technology-enabled hospitality configurations.