RESUMEN
This perspective article on using partial least squares structural equation modelling (PLS-SEM) is intended as a guide for authors who wish to publish datasets that can be analysed with this method as stand-alone data articles. Stand-alone data articles are different from supporting data articles in that they are not linked to a full research article published in another journal. Nevertheless, authors of stand-alone data articles will be required to clearly demonstrate and justify the usefulness of their dataset. This perspective article offers actionable recommendations regarding the conceptualisation phase, the types of data suitable for PLS-SEM and quality criteria to report, which are generally applicable to studies using PLS-SEM. We also present adjusted versions of the HTMT metric for discriminant validity testing that broaden its applicability. Further, we highlight the benefit of linking data articles to already published research papers that employ the PLS-SEM method.
RESUMEN
Corporate reputation is crucial for maintaining and enhancing a company's competitiveness in the marketplace. To actively manage this important intangible asset, which significantly contributes to a company's value, managers need to understand the relationship between reputation and its antecedents and consequences. The dataset presented in this article stems from a conceptual replication of a seminal model of corporate reputation, its antecedents and effects on customer satisfaction and loyalty. Potential mediators and moderators in these relationships allow us to extend the original model in order to clarify the mechanism through which corporate reputation impacts satisfaction and loyalty. We document some of the model's main effects using partial least squares structural equation modeling (PLS-SEM).