PLS-SEM Book: A Primer on PLS-SEM (3rd Ed.)


BRIEF DESCRIPTION OF THE PLS-SEM BOOK:
With applications using SmartPLS (www.smartpls.com)—the primary software used in partial least squares structural equation modeling (PLS-SEM)—this practical guide provides concise instructions on how to use this evolving statistical technique to conduct research and obtain solutions. Featuring the latest research, new examples, and expanded discussions throughout, the third edition is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.

Some comments about the book:
  • "Partial least squares’ modeling is an important statistical technique in management research but one that is most often used by very statistically oriented academicians. The PLS book written by a great team of authors who are all very familiar with using PLS makes the technique more practically understandable. Given the type of data used in management research, this book will facilitate the confident use of PLS by a much larger number of researchers to test holistic multi-equation models." Yves Doz, INSEAD
  • "Partial least squares’ modeling is a great solution technique for a variety of small and large multivariate data problems. This book provides a deeply informed, yet practical, guide to understanding and using PLS for both novice and advanced researchers. This approach to understanding PLS carries one from a preliminary overview of the technique and its application, through the many subtle, but powerful nuances of the method. After 27 years of teaching variations of SEM, I am happy to discover a book that provides a gateway for the novice and a roadmap for the expert to confidently and appropriately model and estimate with PLS in a broad range of research contexts." Roger Calantone, Michigan State University
  • "This PLS book is concise and application-oriented while being scientifically rigorous. With the use of PLS becoming more widespread and important as a tool in the field of management, this PLS book, by a superb author team, gives more scholars the needed practical knowledge to conduct rigorous research on partial least squares modeling." David Ketchen, Auburn University
  • "Partial least squares’ modeling is a very robust and practical technique to tackle many of today’s multi-equation econometric models. In many situations, researchers are interested in both prediction and causality. Since PLS aims to account for the trace (sum of the diagonal in the covariance matrix), it is well suited for prediction. This is in contrast to covariance structure models, where the objective is to account for all the observed variable covariances, which is not particularly relevant for prediction. For the American Customer Satisfaction Index, we have used our own version of PLS since the very beginning. This book, by a great author team, puts PLS more practically into the hands of researchers by creating a logical and understandable way of applying PLS-based predictions based on structural relationships. The result is that we will likely see more use of PLS in research, and significant advances to complex data problems." Claes Fornell, Chairman, CFI Group Worldwide
  • "A text that students will find easy to read and enjoyable." Toni M. Somers,Wayne State University
  • "The book brings new possibilities to analyse data. The book is easy to understand. Even the advanced topics are clear and easy to apply." Professor Lucas Lira Finoti,  FACEAR
  • "The book is well done and good for students who are no experts in statitics." Udo Wagner, University of Vienna
  • "This is great text book, very clear, comprehensive, and can be used both by the new to the field and as a handbook by those who already know the basic concepts. I have recommended this book to my Master students who are writing their dissertations and they were very pleased with it."Carlos Cândido, University of the Algarves
  • "Excellent book covering both material and software previously unavailable in a quality textbook ." Mark Matthews, Argosy University

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