Service with personality: a note on generalizing personality across services contexts

Purpose – This paper aims to address the generalizability of the services personality concept and to propose a way of operationalizing personality across service contexts, not just retail/services brands. Interpersonal services seem especially relevant for analyzing using the personality concept because of the importance of human interaction within these contexts and because personality itself is socially molded. The personality‐based image perception can thus be useful in establishing branding strategies. Design/methodology/approach – An empirical study using exploratory and confirmatory factor analysis provides analytical results based on a sample of over 600 respondents' personality perceptions across three different services categories. A multi‐group SEM approach then tests the resulting measurement theory and examines its generalizability across three different interpersonal service contexts. Findings – The results suggest that the services personality scale: displays strong construct validity; meets criteria for metric invariance across multiple contexts; offers a more complete explanation of service expectations relative to alternative measures; and potentially offers a dynamic explanation of consumers' expectations of the services brand. Practical implications – Managerially, the services personality measure provides a tool for services retailers potentially useful in evaluating their respective service environments and thereby better understanding their relative market positioning. The approach may prove useful for perceptual mapping and competitive analysis. Originality/value – Distinct from the current research that very often concentrates on a single service type using attribute‐based evaluations, this research validates the use of a personality‐based services approach across multiple interpersonal services contexts. Four services personality dimensions are validated which display good generalizability across contexts and good predictive validity as well.