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Advanced Issues in Partial Least Squares Structural Equation Modeling
Joseph F. Hair
Joe Hair, Jr.
Marko Sarstedt
Christian M. Ringle
Siegfried P. Gudergan
出版
Sage
, 2024
主題
Business & Economics / Statistics
Business & Economics / Research & Development
Computers / Mathematical & Statistical Software
Mathematics / Probability & Statistics / Multivariate Analysis
Reference / Research
Social Science / Statistics
ISBN
1071862502
9781071862506
URL
http://books.google.com.hk/books?id=71iszwEACAAJ&hl=&source=gbs_api
註釋
The second edition of Advanced Issues in Partial Least Squares Structural Equation Modeling offers a straightforward and practical guide to PLS-SEM for users ready to go further than the basics of A Primer on Partial Least Squares Structural Equation Modeling, 3rd edition. Even in this advanced guide, the authors have limited the emphasis on equations, formulas, and Greek symbols, and instead rely on detailed explanations of the fundamentals of PLS-SEM and provide general guidelines for understanding and evaluating the results of applying the method. A single study on corporate reputation features as an example throughout the book, along with a single software package (SmartPLS 4.0) to provide a seamless learning experience. The approach of this book is based on the authors' many years of conducting research and teaching methodology courses, including developing the SmartPLS software. The preparation of the book, especially this new edition, is based on the authors' desire to communicate the PLS-SEM method to a much broader audience from management and marketing to engineering, geography, medicine, political and environmental sciences, psychology, and beyond. The second edition includes a new chapter on the necessary condition analysis (NCA) and covers the most recent developments in PLS-SEM, with detailed guidelines for estimating and validating higher-order constructs and nonlinear effects as well as more insights on multigroup and latent class analyses using FIMIX-PLS and PLS-POS. The book is aimed at researchers and practitioners who seek to gain comprehensive knowledge of more advanced PLS-SEM methods.