TY - BOOK ID - 145403575 TI - Partial least squares structural equation modeling (PLS-SEM) using R : a workbook AU - Hair, Joseph F. AU - Hult, G. Tomas M. AU - Ringle, Christian M. AU - Sarstedt, Marko. AU - Danks, Nicholas P. AU - Ray, Soumya. PY - 2021 PB - Cham : Springer International Publishing AG, DB - UniCat KW - Finance KW - Least squares. KW - R (Computer program language) KW - Structural equation modeling. KW - Open Access KW - PLS-SEM) Using R KW - Workbook KW - Partial Least Squares Structural Equation Modeling KW - R Software Environment KW - Mathematical models. KW - Open Access KW - PLS-SEM) Using R KW - Workbook KW - Partial Least Squares Structural Equation Modeling KW - R Software Environment UR - https://www.unicat.be/uniCat?func=search&query=sysid:145403575 AB - Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method's flexibility in terms of data requirements and measurement specification. This practical open access guide provides a step-by-step treatment of the major choices in analyzing PLS path models using R, a free software environment for statistical computing, which runs on Windows, macOS, and UNIX computer platforms. Adopting the R software's SEMinR package, which brings a friendly syntax to creating and estimating structural equation models, each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Simple instructions give readers the "how-tos" of using SEMinR to obtain solutions and document their results. Rules of thumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM ER -