Developing a service quality scale for artificial intelligence service agents

Purpose Service providers and consumers alike are increasingly adopting artificial intelligence service agents (AISA) for service. Yet, no service quality scale exists that can fully capture the key factors influencing AISA service quality. This study aims to address this shortcoming by developing a scale for measuring AISA service quality (AISAQUAL). Design/methodology/approach Based on extant service quality research and established scale development techniques, the study constructs, refines and validates a multidimensional AISAQUAL scale through a series of pilot and validation studies. Findings AISAQUAL contains 26 items across six dimensions: efficiency, security, availability, enjoyment, contact and anthropomorphism. The new scale demonstrates good psychometric properties and can be used to evaluate service quality across AISA, providing a means of examining the relationships between AISA service quality and satisfaction, perceived value as well as loyalty. Research limitations/implications Future research should validate AISAQUAL with other AISA types, as they diffuse throughout the service sector. Moderating factors related to services, the customer and the AISA can be investigated to uncover the boundary conditions under which AISAQUAL is likely to influence service outcomes. Longitudinal studies can be carried out to assess how ongoing use of AISA can change service outcomes. Practical implications Service managers can use AISAQUAL to effectively monitor, diagnose and improve services provided by AISA while enhancing their understanding of how AISA can deliver better service quality and customer loyalty outcomes. Originality/value Anthropomorphism is identified as a new service quality dimension. AISAQUAL facilitates theory development by providing a reliable scale to improve the current understanding of consumers’ perspectives concerning AISA services.