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Advanced Issues in Partial Least Squares Structural Equation Modeling Joe Hair

Advanced Issues in Partial Least Squares Structural Equation Modeling By Joe Hair

Advanced Issues in Partial Least Squares Structural Equation Modeling by Joe Hair


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Summary

A practical and applied text on PLS-SEM that combines simple explanations of complex statistical concepts with examples and case studies that readers can follow using datasets available with the book.

Advanced Issues in Partial Least Squares Structural Equation Modeling Summary

Advanced Issues in Partial Least Squares Structural Equation Modeling by Joe Hair

Provides a concise yet very practical, guide to understanding and applying advance concepts and approaches of PLS structural equation modelling, This text includes extensive examples on SmartPLS 3 software, and is accompanied by multiple data sets that the user can download from the accompanying website.

About Joe Hair

Joseph F. Hair, Jr. is Cleverdon Chair of Business, and Director of the PhD Degree in Business Administration, Mitchell College of Business, University of South Alabama. He previously held the Copeland Endowed Chair of Entrepreneurship and was Director, Entrepreneurship Institute, Ourso College of Business Administration, Louisiana State University. Joe was recognized by Clarivate Analytics in 2018, 2019 and 2020 for being in the top 1% globally of all Business and Economics professors based on his citations and scholarly accomplishments, which exceed 238,000 over his career. He has authored more than 75 books, including Multivariate Data Analysis (8th edition, 2019) (cited 140,000+ times), MKTG (13th edition, 2020), Essentials of Business Research Methods (2020), and Essentials of Marketing Research (4th edition, 2020). 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. He has a new book on Marketing Analytics, forthcoming in 2021 (McGraw-Hill). Marko Sarstedt is a chaired Professor of Marketing at the Otto-von-Guericke-University Magdeburg (Germany) and an Adjunct Professor at Babe?-Bolyai University, Romania. His main research interest is the advancement of research methods to enhance the understanding of consumer behavior. His research has been published in Nature Human Behavior, Journal of Marketing Research, Journal of the Academy of Marketing Science, Multivariate Behavioral Research, Organizational Research Methods, MIS Quarterly, and Psychometrika, among others. His research ranks among the most frequently cited in the social sciences with more than 70,000 citations according to Google Scholar. Professor Sarstedt has won numerous best paper and citation awards, including five Emerald Citations of Excellence awards and two AMS William R. Darden Awards. According to the 2020 F.A.Z. ranking, he is the second most influential researcher in Germany, Austria, and Switzerland. Professor Sarstedt has been named member of Clarivate Analytics' Highly Cited Researchers List, which includes the world's most impactful scientific researchers. Christian M. Ringle is a chaired Professor of Management at the Hamburg University of Technology (Germany) and an Adjunct Professor at the University of Waikato (New Zealand). 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, Professor 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 Christian M. Ringle can be found at https://www.tuhh.de/hrmo/team/prof-dr-c-m-ringle.html. Siegfried P. Gudergan is a Chaired Professor of Strategy at Newcastle Business School within the University of Newcastle (Australia). He previously was Head of School and Professor of Marketing at UTS Business School within the University of Technology, Sydney (Australia). He holds a PhD from the Australian Graduate School of Management that was awarded by both the University of Sydney and the University of New South Wales. His research focuses on managerial decision-making and is applied to strategic management issues. Some of his work that concerns PLS-SEM has appeared in journals such the Journal of the Academy of Marketing Science, Long Range Planning and Journal of Business Research. He has been the primary advisor for doctoral students who have been awarded, for example, an Honorable Mention as finalist for the Dissertation Award of the Academy of Management's Business Policy & Strategy Division and the Best PhD Paper Award by the Strategic Management Society.

Table of Contents

Preface About the Authors Chapter 1: An Overview of Recent and Emerging Developments in PLS-SEM Chapter Preview Origins and Evolution of Partial Least Squares Structural Equation Modeling Measurement Model Estimation PLS-SEM or CB-SEM? Organization of the Remaining Chapters Case Study Illustration Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 2: Advanced Modeling Chapter Preview Hierarchical Component Models Nonlinear Relationships Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 3: Advanced Model Assessment Chapter Preview Confirmatory Tetrad Analysis Importance-Performance Map Analysis Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 4: Modeling Observed Heterogeneity Chapter Preview Observed and Unobserved Heterogeneity Testing Measurement Model Invariance Nonparametric Tests Case Study Illustration-Invariance Assessment and Multigroup Analysis Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 5: Modeling Unobserved Heterogeneity Chapter Preview Case Study Illustration-Latent Class Analysis Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Glossary References Author Index Subject Index

Additional information

NGR9781483377391
9781483377391
1483377393
Advanced Issues in Partial Least Squares Structural Equation Modeling by Joe Hair
New
Paperback
SAGE Publications Inc
2017-06-28
272
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
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