Hair / Hult / Ringle A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)

3. Third Auflage 2021
ISBN: 978-1-5443-9641-5
Verlag: SAGE Publications
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 384 Seiten, EPUB

The third edition of 
A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) guides readers through learning and mastering the techniques of this approach in clear language. Authors Joseph H. Hair, Jr., G. Tomas M. Hult, Christian Ringle, and Marko Sarstedt use their years of conducting and teaching research to communicate the fundamentals of PLS-SEM in straightforward language to explain the details of this method, with limited emphasis on equations and symbols. A running case study on corporate reputation follows the different steps in this technique so readers can better understand the research applications. Learning objectives, review and critical thinking questions, and key terms help readers cement their knowledge. This edition has been thoroughly updated, featuring the latest version of the popular software package SmartPLS 3. New topics have been added throughout the text, including a thoroughly revised and extended chapter on mediation, recent research on the foundations of PLS-SEM, detailed descriptions of research summarizing the advantages as well as limitations of PLS-SEM, and extended coverage of advanced concepts and methods, such as out-of-sample versus in-sample prediction metrics, higher-order constructs, multigroup analysis, necessary condition analysis, and endogeneity.

Autoren/Hrsg.

Hair, Joe

Hult, G. Tomas M.

Ringle, Christian M.

Sarstedt, Marko

Inhaltsverzeichnis

Preface

About the Authors

Chapter 1. An Introduction to Structural Equation Modeling

Chapter Preview

What Is Structural Equation Modeling?

Considerations in Using Structural Equation Modeling

Principles of Structural Equation Modeling

PLS-SEM, CB-SEM, and Regressions Based on Sum Scores

Considerations When Applying PLS-SEM

Guidelines for Choosing Between PLS-SEM and CB-SEM

Organization of Remaining Chapters

Summary

Review Questions

Critical Thinking Questions

Key Terms

Suggested Readings

Chapter 2. Specifying the Path Model and Examining Data

Chapter Preview

Stage 1: Specifying the Structural Model

Stage 2: Specifying the Measurement Models

Stage 3: Data Collection and Examination

Case Study Illustration—Specifying the PLS-SEM Model

Summary

Review Questions

Critical Thinking Questions

Key Terms

Suggested Readings

Chapter 3. Path Model Estimation

Chapter Preview

Stage 4: Model Estimation and the PLS-SEM Algorithm

Case Study Illustration—PLS Path Model Estimation (Stage 4)

Summary

Review Questions

Critical Thinking Questions

Key Terms

Suggested Readings

Chapter 4. Assessing PLS-SEM Results—Part I: Evaluation of the Reflective Measurement Models

Chapter Preview

Overview of Stage 5: Evaluation of Measurement Models

Stage 5a: Assessing Results of Reflective Measurement Models

Case Study Illustration—Evaluation of the Reflective Measurement Models (Stage 5a)

Summary

Review Questions

Critical Thinking Questions

Key Terms

Suggested Readings

Chapter 5. Assessing PLS-SEM Results—Part II: Evaluation of the Formative Measurement Models

Chapter Preview

Stage 5b: Assessing Results of Formative Measurement Models

Case Study Illustration—Evaluation of the Formative Measurement Models (Stage 5b)

Summary

Review Questions

Critical Thinking Questions

Key Terms

Suggested Readings

Chapter 6. Assessing PLS-SEM Results—Part III: Evaluation of the Structural Model

Chapter Preview

Stage 6: Structural Model Results Evaluation

Case Study Illustration—Evaluation of the Structural Model (Stage 6)

Summary

Review Questions

Critical Thinking Questions

Key Terms

Suggested Readings

Chapter 7. Mediator and Moderator Analysis

Chapter Preview

Mediation

Moderation

Case Study Illustration—Moderation

Summary

Review Questions

Critical Thinking Questions

Key Terms

Suggested Readings

Chapter 8. Outlook on Advanced Methods

Chapter Preview

Importance-Performance Map Analysis

Necessary Condition Analysis

Higher-Order Constructs

Confirmatory Tetrad Analysis

Examining Endogeneity

Treating Observed and Unobserved Heterogeneity

Measurement Model Invariance

Consistent PLS-SEM

Summary

Review Questions

Critical Thinking Questions

Key Terms

Suggested Readings

Glossary

References

Index

Über Autor(innen)

Ringle, Christian M.

Christian M. Ringle is Professor of Management at the Hamburg University of Technology (Germany). His research addresses management of organizations, human resource management, methods development for business analytics and their application to business research. His contributions in these fields have been published in journals such as International Journal of Research in Marketing, Information Systems Research, Journal of the Academy of Marketing Science, MIS Quarterly, Organizational Research Methods, and The International Journal of Human Resource Management. Since 2018, he has been named member of Clarivate Analytics’ Highly Cited Researchers List. In 2014, Ringle co-founded SmartPLS (http://www.smartpls.com), a software tool with a graphical user interface for the application of the partial least squares structural equation modeling (PLS-SEM) method. Besides supporting consultancies and international corporations, he regularly teaches doctoral seminars on business analytics and multivariate statistics, the PLS-SEM method, and the use of SmartPLS worldwide. More information about Professor Dr. Christian M. Ringle can be found at https://www.tuhh.de/hrmo/team/prof-dr-c-m-ringle.html.

Hair, Joe

Joseph F. Hair, Jr.is Professor of Marketing, PhD Director, and the Cleverdon Chair of Business in the Mitchell College of Business, University of South Alabama, USA. He previously held the Copeland Endowed Chair of Entrepreneurship and was Director, Entrepreneurship Institute, Ourso College of Business Administration, Louisiana State University. He has authored over 95 books, including Multivariate Data Analysis (8^th edition, 2019) (cited 170,000+ times), MKTG (13^th edition, 2019), Essentials of Business Research Methods, 5^th edition, 2023), and Essentials of Marketing Research (6^th edition, 2023). Dr. Hair is the most highly cited scholar in PLS-SEM and marketing, with 340,000+ citations (Google Scholar, 2023). He also has published numerous articles in scholarly journals and was recognized as the Academy of Marketing Science Marketing Educator of the year. A popular guest speaker, Professor Hair often presents seminars on research techniques, multivariate data analysis, and marketing issues for organizations in Europe, Australia, China, India, and South America.

Sarstedt, Marko

Marko Sarstedt is Professor of Marketing at the Ludwig-Maximilians-University Munich (Germany) and an adjunct research professor at Babe?-Bolyai-University Cluj-Napoca (Romania). His main research interest is the advancement of research methods to further the understanding of consumer behavior. His research has been published in Nature Human Behaviour, Journal of Marketing Research, Journal of the Academy of Marketing Science, Multivariate Behavioral Research, Organizational Research Methods, MIS Quarterly, British Journal of Mathematical and Statistical Psychology, and Psychometrika, among others. His research ranks among the most frequently cited in the social sciences with more than 100,000 citations according to Google Scholar. Marko has won numerous best paper and citation awards, including five Emerald Citations of Excellence awards and two AMS William R. Darden Awards. Marko has been repeatedly named member of Clarivate Analytics’ Highly Cited Researchers List. In March 2022, he was awarded an honorary doctorate from Babe?-Bolyai-University Cluj-Napoca for his research achievements and contributions to international exchange.

Hult, G. Tomas M.

G. Tomas M. Hult is Professor and Byington Endowed Chair at Michigan State University (USA), and holds a visiting Chaired Professorship at Leeds University Business School (United Kingdom) and a visiting professorship at Uppsala University (Sweden). Professor Hult is a member of the Expert Networks of the World Economic Forum and United Nations/UNCTAD’s World Investment Forum, and is also part of the Expert Team at the American Customer Satisfaction Index (ACSI). Dr. Hult was recognized in 2016 as the Academy of Marketing Science / CUTCO-Vector Distinguished Marketing Educator; he is an elected Fellow of the Academy of International Business; and he ranks in the top-10 scholars in marketing per the prestigious “world ranking of scientists.” At Michigan State University, Dr. Hult was recognized with the Beal Outstanding Faculty Award in 2019 (MSU’s highest award ”for outstanding total service to the University“), and he has also been recognized with the John Dunning AIB Service Award for outstanding service to AIB – as the longest serving Executive Director in AIB’s history (2004-2019) (the most prestigious service award given by the Academy of International Business). Professor Hult regularly teaches doctoral seminars on multivariate statistics, structural equation modeling, and hierarchical linear modeling worldwide. He is a dual citizen of Sweden and the United States. More information about Professor Hult can be found at http://www.tomashult.com.