Recent Advances and Applications in Partial Least Squares Structural Equation Modeling (PLS-SEM)

Dear Colleagues,

Partial Least Squares Structural Equation Modeling (PLS-SEM) represents a new generation statistical data analysis technique that, despite its recent creation, is gaining popularity in academia exponentially: it has attracted the interest of scholars in various methodologies, becoming a vivid and constantly evolving technique. In today's world, managers of companies and public administrations, academics, and researchers have at their disposal a large amount of data to analyze for decision-making and the discovery of new findings. This requires the establishment of a theoretical framework, the use of sciences such as mathematics and statistics, as well as experience and intuition. In this regard, PLS-SEM involves a multivariate data analysis technique that combines the methodologies of regression and linear analysis. It is widely employed in the fields of business, management and accounting, social sciences, economics, finance, environmental sciences, medicine and health professions, etc., where it is necessary to handle unobservable or latent variables. It allows jointly analyzing the relationships between observable and latent variables (evaluation of the measurement model) and the relationships between latent variables (evaluation of the structural model). Thus, this special and multidisciplinary issue focuses on the application of PLS-SEM, providing a platform for researchers to present their novel and unpublished papers with attractive results.

Dr. María del Carmen Valls Martínez
Prof. Dr. José-María Montero
Dr. Pedro Antonio Martín Cervantes
Topic Editors