Comparison of Composites, Dichotomous, and Latent Factor Measurement Operationalizations in Hospitality Research on Moderating Effects

Abstract

Moderation testing through latent factor models is relatively underutilized in hospitality and tourism research. The purpose of this research is to highlight the differences in the treatment of measurements of reflective constructs as composite indices versus latent factors in moderating effect tests in hospitality research. For this research, we build our primer on the investigation of the differences in customer satisfaction with the perceived entertainment experience at a hospitality/tourism attraction, contingent on customers’ personality trait extraversion, borrowed from the Big-Five mini marker inventory. Our findings illustrate the consequences of the measurement conceptualization and the representation of constructs in statistical models with interaction effects. While using composites simplifies the estimation of the regression paths and provides a reasonable sense of the direction of the effect and its statistical significance, it is not always aligned with the theoretical and conceptual underpinning of the employed constructs. A statistical model with composites may underestimate an interaction effect, whereas a model with a dichotomized moderator may overestimate the interaction effect. The findings of this research draw the attention of the hospitality and tourism research community on different representations of reflective constructs in their measurement and statistical models.