Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2 ed.). Thousand Oaks, CA: Sage.

A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) by Joseph F. Hair, Jr., G. Tomas M. Hult, Christian Ringle, and Marko Sarstedt is a practical guide that provides concise instructions on how to use partial least squares structural equation modeling (PLS-SEM), an evolving statistical technique, to conduct research and obtain solutions. Featuring the latest research, new examples using the SmartPLS software, and expanded discussions throughout, the Second Edition is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.

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Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2018). Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM). Thousand Oaks, CA: Sage.

Written as an extension of A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) Second Edition, this easy-to-understand, practical guide covers advanced content on PLS-SEM to help students and researchers apply techniques to research problems and accurately interpret results. Authors Joseph F. Hair, Jr., Marko Sarstedt, Christian Ringle, and Siegfried P. Gudergan provide a brief overview of basic concepts before moving to the more advanced material. Offering extensive examples on SmartPLS 3 software and accompanied by free downloadable data sets, the book emphasizes that any advanced PLS-SEM approach should be carefully applied to ensure that it fits the appropriate research context and the data characteristics that underpin the research.

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Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Richter, N. F., & Hauff, S. (2017). Partial Least Squares Strukturgleichungsmodellierung (PLS-SEM): Eine anwendungsorientierte Einführung. München: Vahlen.

Dieses Buch liefert eine anwendungsorientierte Einführung in die PLS-SEM. Der Fokus liegt auf den Grundlagen des Verfahrens und deren praktischer Umsetzung mit Hilfe der SmartPLS-Software. Das Konzept des Buches setzt dabei auf einfache Erläuterungen statistischer Ansätze und die anschauliche Darstellung zahlreicher Anwendungsbeispiele anhand einer einheitlichen Fallstudie. Viele Grafiken, Tabellen und Illustrationen erleichtern das Verständnis der PLS-SEM. Zudem werden dem Leser herunterladbare Datensätze, Videos, Aufgaben und weitere Fachartikel zur Vertiefung angeboten. Damit eignet sich das Buch hervorragend für Studierende, Forscher und Praktiker, die die PLS-SEM zur Gewinnung von Ergebnissen mit den eigenen Daten und Modellen nutzen möchten. SmartPLS ist das führende Softwareprogramm zur Schätzung von PLS-basierten Strukturgleichungsmodellen. Die Erläuterungen und die im Buch vorgeschlagenen Vorgehensweisen spiegeln den aktuellen Stand der Forschung wider.

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Ramayah, T., Cheah, J., Chuah, F., Ting, H., & Memon, M. A. (2018). Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 3.0: An Updated Guide and Practical Guide to Statistical Analysis (2nd Edition). Kuala Lumpur, Malaysia: Pearson.

This book is unique in a sense that it encapsulates four elements in a concise manner. Firstly, it provides step-by-step guidance and explanation to statistical analysis using SmartPLS 3.0. Secondly, it is highly graphical as each section related to the use of SmartPLS is illustrated by screenshots of the software interface and/or output. Thirdly, it incorporates our experience as users of SmartPLS into the writing so as to make every explanation more practical and comprehensible. Fourthly, we provide citations, reading materials and references throughout the manual to substantiate our explanation and to facilitate the readers to read them in greater detail.

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Garson, G. D. (2016). Partial Least Squares Regression and Structural Equation Models. Asheboro: Statistical Associates.

This handbook provides a comprehensive overview of Partial Least Squares (PLS) methods with specific reference to their use in marketing and with a discussion of the directions of current research and perspectives.

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Avkiran, N. K., & Ringle, C. M. (Eds.). (2018). Partial Least Squares Structural Equation Modeling: Recent Advances in Banking and Finance. Heidelberg: Springer.

Partial Least Squares Structural Equation Modeling (PLS-SEM) is already a popular tool in marketing and management information systems used to explain latent constructs. Until now, PLS-SEM has not enjoyed a wide acceptance in Banking and Finance. Based on recent research developments, this book represents the first collection of PLS-SEM applications in Banking and Finance. This book will serve as a reference book for those researchers keen on adopting PLS-SEM to explain latent constructs in Banking and Finance.

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Latan, H., & Noonan, R. (Eds.). (2017). Partial Least Squares Structural Equation Modeling: Basic Concepts, Methodological Issues and Applications. Heidelberg: Springer.

This edited book presents the recent developments in partial least squares structural equation modeling (PLS-SEM) and provides a comprehensive overview of the current state of the most advanced research related to PLS-SEM.

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Esposito Vinzi, V., Chin, W. W., Henseler, J., & Wang, H. (Eds.). (2010). Handbook of Partial Least Squares: Concepts, Methods and Applications (Springer Handbooks of Computational Statistics Series, vol. II). Heidelberg, Dordrecht, London, New York: Springer.

This is a graduate-level introduction and illustrated tutorial on partial least squares (PLS). PLS may be used in the context of variance-based structural equation modeling, in contrast to the usual covariance-based structural equation modeling, or in the context of implementing regression models. PLS is largely a nonparametric approach to modeling, not assuming normal distributions in the data, often recommended when the focus of research is prediction rather than hypothesis testing, when sample size is not large, or in the presence of noisy data.

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