【Ebook SmartPLS】A Primer on PLS-SEM (3e)

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 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.

DESCRIPTION

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.

CONTENTS

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

NEW TO THIS EDITION

All screenshots and instructions have been updated for the latest edition of Smart PLS software, SmartPLS 3.
A thoroughly revised and updated Chapter 7 on Mediator and Moderator Analysis covers more types of mediation, and provides updated explanations and guidelines on moderated mediation.
The latest research on the nature of composite-based modeling provides a more thorough conceptual foundation for PLS-SEM
Applications of PLS-SEM with secondary or archival data shows readers even more applications for this approach
Coverage of model fit, analysis of predictive power, and metrics of model comparison have all been expanded for a richer discussion of PLS-SEM
Improved guidelines for generating and validating single-item measures for redundancy analyses and determining minimum sample sizes help clarify these steps
More on the distinction between PLS-SEM and CB-SEM helps readers choose the right technique for their project
Extended coverage of more advanced concepts helps readers go further with PLS-SEM
Summaries are now structured by learning outcome for improved organization

KEY FEATURES

Simple instructions give readers the “how-tos” of using the SmartPLS software (www.smartpls.com) to obtain solutions, and prepare manuscripts using PLS-SEM for academic journal submissions.
Rules of Thumb in every chapter provide guidelines on best practices in the application and interpretation of PLS-SEM.
A focus on accessibility is reflected through limited equations, formulas, and Greek symbols to facilitate clear understanding.
Chapters organized around learning outcomes simplify the process of learning the concepts and statistical terms.
Concepts consistently defined in plain language further facilitate comprehension of methods.

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