Partial Least Squares Structural Equation Modeling (PLS-SEM) Applications in Economics and Finance

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 field of social sciences, 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). Likewise, it is a widespread approach in management, since it allows the study of complex models with innumerable indicators for each latent variable and numerous relationships among latent variables. Thus, this Special Issue focuses on the application of PLS-SEM in Economics and Finance, providing a platform for researchers to present their novel and unpublished papers with attractive results.

Prof. Dr. María del Carmen Valls Martínez
Dr. Pedro Antonio Martín Cervantes
Guest Editors

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