**Preface**

Partial Least Squares Structural Equation Modeling (PLS-SEM) is an innovative approach to statistical data analysis that has gained rapid popularity in academic circles, despite its recent origin. This method has captured the attention of scholars across various disciplines and continues to dynamically evolve.

In the contemporary landscape, decision makers in businesses, public sectors, academics and researchers have access to copious amounts of data for analysis and discovery. Therefore, this necessitates a robust theoretical framework and the application of disciplines such as mathematics and statistics, as well as practical experience and intuition. PLS-SEM stands out as a multivariate analysis technique that combines regression and linear analysis methodologies, offering advantages (such as not mandating normality) and yielding dependable results even with small sample sizes. This technique is extensively used in social sciences, particularly for handling unobservable or latent variables. PLS-SEM facilitates the simultaneous examination of relationships between observable and latent variables (assessing the measurement model) as well as relationships among latent variables (evaluating the structural model). Moreover, it is widely embraced in management due to its capacity to scrutinize intricate models with numerous indicators for each latent variable and multiple relationships among them.

This book encompasses 23 research articles and 1 review selected for publication from a total of 56 manuscripts submitted to the MDPI Special Issue, entitled "Recent Advances and Applications in Partial Least Squares Structural Equation Modeling (PLS-SEM)." These 24 papers, previously published in the journals *Economies* (7 papers), *Mathematics* (6 papers), *Sustainability* (10 papers) and *Data* (1 paper), explore diverse themes related to the theory and practical application of PLS-SEM methodology. These topics include the prediction of stock market investment intentions, the nexus between institutional quality and international competitiveness, governance paradigms, information and communication technologies in the supply chain, impacts of environmental information absorption and proactivity on company outcomes, quality management, corporate social responsibility's effects on financial performance, healthcare system enhancement through resource management, self-awareness in online shopping behavior, status quo as a predictor of brand loyalty and innovation propensity, utilization of maximum entropy bootstrapping for time series, etc.

This book is considered a valuable resource for professionals in PLS-SEM, spanning various domains such as economics, finance, marketing, education, etc. It covers applications involving higher-order constructs, mediating variables, multigroup analysis and the latest advancements in applied methodology.

As Guest Editors of this Special Issue, we extend our gratitude to the contributing authors for their high-quality submissions, the reviewers for their invaluable feedback that enhanced the manuscripts and the administrative team at MDPI for their support of this project. Special gratitude is owed to Dr. Syna Mu, the Managing Editor of this Special Issue, for his professionalism, interpersonal skills, outstanding collaboration and valuable assistance.
