Customers perceptions about robots and employees in the frontline: attributions of responsibility and stability after service success and failure
(A2020-64088)

AUTHORS

Daniel Belanche, University of Zaragoza; Luis V. Casaló, University of Zaragoza; Carlos Flavián, Universidad de Zaragoza; Jeroen Schepers, Eindhoven University of Technology

KEYWORDS

Frontline robots; service failure; artificial intelligence

ABSTRACT

Robots are taking over the organizational frontline. The purpose of this research is to provide valuable empirical insights by building on attribution theory. Two experimental studies were addressed to US customers. Vignette-based scenarios focusing on a hotel’s reception service and restaurant’s waiter service were employed. Results indicate that customers make stronger attributions of responsibility for the service performance towards humans than towards robots, especially when a service failure occurs. This implies that people attribute responsibility to the firm rather than the frontline robot. Interestingly, the perceived stability of the performance is greater when the service is conducted by a robot than by an employee. To avoid harmful customer attributions, service providers should clearly communicate to customers that frontline robots pack sophisticated analytical, rather than simple mechanical, artificial intelligence technology that explicitly learns from service failures.