Partial least squares path modelling (PLSPM)

Abstract

The use of partial least squares path modelling (PLSPM) has escalated in the areas of marketing, management, information systems, and organizational behaviour. Researchers in tourism and hospitality have to date been reluctant to use this approach, instead, focusing on covariance-based structural equation modelling (CBSEM) techniques conducted in Lisrel or AMOS. This article highlights the main differences between CBSEM and PLSPM and describes the advantages of PLSPM with regard to (1) testing theories and analyzing structural relationships among latent constructs; (2) dealing with sample size limitations and non-normal data; (3) analyzing complex models that have 'formative' and 'reflective' latent constructs; and (4) analyzing models with higher-order molar and molecular constructs. These advantages are put into practice using examples from a tourism context. The paper demonstrates the application of PLSPM in the case of destination competitiveness, and illustrates how this approach could enhance the theoretical and practical usefulness of tourism modelling. This paper also presents a step-by -step guide to PLSPM analysis, providing directions for future research designs in tourism. This presents valuable knowledge for researchers, editors, and reviewers with recommendations, rules of thumb, and corresponding references for appropriately applying and assessing structural models