Construction and validation of an updated perfect automation schema (uPAS) scale

Abstract

Abstract The perfect automation schema is described as a representation people hold regarding the performance of automated systems, comprising initial high expectations for automated systems’ performance and low forgiveness after automated systems fail. Merritt, Unnerstall, Lee, and Huber have created a self-report measure of perfect automation schema comprising the two aforementioned factors, but this measure has demonstrated poor internal consistency estimates. In the present research, we created an updated perfect automation schema (uPAS) scale that showed acceptable reliability and validity estimates. In Study 1, we generated items that described both factors of perfect automation schema and conducted an exploratory factor analysis. In Study 2, we conducted a confirmatory factor analysis to confirm the uPAS scale composition and examined the scale’s convergent, discriminant, and criterion validity. We found acceptable reliability estimates for the new scale across both studies. In Study 2, however, we found the uPAS scale factors and the factors from Merritt and colleagues’ scale showed similar criterion validity across three trust-related criteria (trustworthiness perceptions, reliance intentions, and use endorsement). We conclude by offering a reliable uPAS scale to assess the perfect automation schema, which showed comparable criterion-related validity to Merritt and colleagues’ scale.