Beyond Factors: IGSCA-SEM’s Application in The Context of Cannabis Tourism

Abstract

Structural Equation Modeling (SEM) is a statistical technique that is used to model the relationships among hypothetical constructs investigated by researchers. SEM can be broadly classified into two main approaches: factor-based (or covariance-based) SEM and component-based (or variance-based) SEM. Factor-based SEM is particularly well-suited for analyzing constructs that resemble factors, while component-based SEM is designed for composites or components. Historically, in the field of tourism research, there has been a tendency to treat factor models as a statistical proxy for all types of hypothetical constructs. However, when the hypothetical construct is incorrectly modeled as a factor instead of a composite, which is its appropriate representation, it can result in bias in parameter estimates. The information presented in this study highlights that this practice has persisted even in top-tier tourism journals, including articles published in the ABAC journal. Contemporary practices that align with the current research landscape in tourism are synthesized. These practices acknowledge that hypothetical constructs can either be factors or components. To illustrate this, a hypothetical example related to cannabis tourism is used, modelling it using mixed constructs based on IGSCA-SEM. Researchers are consequently encouraged to employ SEM, particularly when aiming to publish in the ABAC journal, to enhance their methodological rigor by adopting the recommended practices outlined.