Structural equation modeling (SEM) is a statistical analytic framework that allows researchers to specify and test models with observed and latent (or unobservable) variables and their generally linear relationships. In the past decades, SEM has become a standard statistical analysis technique...

Applications of the partial least squares (PLS) path modeling approach — which have gained increasing dissemination in business research — usually build on the assumption that the data stem from a single population. However, in empirical applications, this assumption of homogeneity is...

Purpose: Generalized structured component analysis (GSCA) and partial least squares path modeling (PLSPM) are two key component-based approaches to structural equation modeling that facilitate the analysis of theoretically established models in terms of both explanation and prediction. This...

With the increasing prominence of partial least squares structural equation modeling (PLS-SEM) in business research, the use of latent class analyses for identifying and treating unobserved heterogeneity has also gained momentum. Researchers have introduced various latent class approaches in a...

PurposePartial least squares structural equation modeling (PLS-SEM) has attracted much attention from both methodological and applied researchers in various disciplines – also in hospitality management research. As PLS-SEM is relatively new compared to other multivariate analysis techniques,...

With economic considerations exerting an ever-increasing influence on soccer clubs’ activities, fan satisfaction becomes an essential strategic management objective for these institutions. Despite this topic’s obvious relevance, the literature has paid little attention to the measurement of...