A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd Revised edition)

A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd Revised edition)

By: Prof Joseph F. Hair (author), G. Tomas M. Hult (author), Christian M. Ringle (author), Marko Sarstedt (author), Joe Hair (author)Paperback

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Description

The authors explain the statistical modeling technique and the fundamental aspects of the methods in a straightforward manner that is accessible to individuals with limited statistical and mathematical training. They clarify the nature and role of PLS-SEM in social sciences research that allows researchers to pursue research in new and different ways. In order to facilitate learning, a single case study has been used throughout the book. Changes in the 2nd edition include: *an overview of the latest research on composite-based modelling *more coverage of the distinction between PLS-SEM and CB-SEM *introduction of a new criterion for discrimination validity assessment *revision and extension of the chapter on mediation *extended description of moderation *a brief introduction to some more advanced techniques

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About Author

Joe F. Hair, Jr. is Professor of Marketing, DBA Director and the Cleverdon Chair of Business in the Mitchell College of Business, University of South Alabama. He previously was Senior Scholar, DBA Program, Coles College of Business, Kennesaw State University, held the Copeland Endowed Chair of Entrepreneurship and was Director, Entrepreneurship Institute, Ourso College of Business Administration, Louisiana State University. He has authored over 60 books, including Multivariate Data Analysis (7th edition, 2010) (cited 140,000+ times), MKTG (10th edition, 2016), Essentials of Business Research Methods (2016), and Essentials of Marketing Research (4th edition, 2017). 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. Dr. G. Tomas M. Hult is Professor and Byington Endowed Chair in International Business and Director of the International Business Center in the Eli Broad College of Business at Michigan State University. He has been Executive Director of the Academy of International Business and President of the AIB Foundation since 2004, was Editor-in-Chief of the Journal of the Academy of Marketing Science from 2009 to 2015, and has been on the U.S. Department of Commerce's District Export Council since 2012. Professor Hult is one of some 80 elected Fellows of the Academy of International Business. He is one of the world's leading authorities in global strategy, with a particular focus on topics dealing with the intersection of global strategy and supply chain management. In various ranking studies, Hult is listed as one of the top-cited authors in business and economics (e.g., Thomson Reuters). He regularly teaches doctoral seminars on multivariate statistics, structural equation modeling, and hierarchical linear modeling worldwide. Dr. Hult is a dual citizen of Sweden and the United States. More information about Tomas Hult can be found at http://www.tomashult.com Christian M. Ringle is a Chaired Professor of Management at the Hamburg University of Technology (Germany) and Conjoint Professor at the Faculty of Business Law at the University of Newcastle (Australia). He holds a master's degree in business administration from the University of Kansas and received his doctor of philosophy from the University of Hamburg (Germany). His widely published research addresses the management of organizations, strategic and human resource management, marketing, and quantitative methods for business and market research. He is cofounder of 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 multivariate statistics, the PLS-SEM method, and the use of SmartPLS worldwide. More information about Christian M. Ringle and his full list of publications can be found at http://www.tuhh.de/hrmo/team/prof-dr-c-m-ringle.html. Marko Sarstedt is Chaired Professor of Marketing at the Otto-von-Guericke-University Magdeburg (Germany) and Conjoint Professor to the Faculty of Business and Law at the University of Newcastle (Australia). He previously was an Assistant Professor of Quantitative Methods in Marketing and Management at the Ludwig-Maximilians-University Munich (Germany). His main research is in the application and advancement of structural equation modeling methods to further the understanding of consumer behavior and to improve marketing decision-making. His research has been published in journals such as Journal of Marketing Research, Journal of the Academy of Marketing Science, Organizational Research Methods, MIS Quarterly, International Journal of Research in Marketing, Long Range Planning, Journal of World Business, and Journal of Business Research. According to the Handelsblatt ranking, Sarstedt is among the top three young academic marketing researchers in Germany. He regularly teaches doctoral seminars on multivariate statistics, structural equation modeling, and measurement worldwide.

Contents

Chapter 1: An Introduction to Structural Equation Modeling What Is Structural Equation Modeling? Considerations in Using Structural Equation Modeling Structural Equation Modeling With Partial Least Squares Path Modeling PLS-SEM, CB-SEM, and Regressions Based on Sum Scores Organization of Remaining Chapters Chapter 2: Specifying the Path Model and Examining Data 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 Path Model Creation Using the SmartPLS Software Chapter 3: Path Model Estimation Stage 4: Model Estimation and the PLS-SEM Algorithm Case Study Illustration: PLS Path Model Estimation (Stage 4) Chapter 4: Assessing PLS-SEM Results Part I: Evaluation of Reflective Measurement Models Overview of Stage 5: Evaluation of Measurement Models Stage 5a: Assessing Results of Reflective Measurement Models Case Study Illustration-Reflective Measurement Models Running the PLS-SEM Algorithm Reflective Measurement Model Evaluation Chapter 5: Assessing PLS-SEM Results Part II: Evaluation of the Formative Measurement Models Stage 5b: Assessing Results of Formative Measurement Models Bootstrapping Procedure Bootstrap Confidence Intervals Case Study Illustration-Evaluation of Formative Measurement Models Chapter 6: Assessing PLS-SEM Results Part III: Evaluation of the Structural Model Stage 6: Assessing PLS-SEM Structural Model Results Case Study Illustration-How Are PLS-SEM Structural Model Results Reported? Chapter 7: Mediator and Moderator Analysis Mediation Moderation Chapter 8: Outlook on Advanced Methods Importance-Performance Map Analysis Hierarchical Component Models Confirmatory Tetrad Analysis Dealing With Observed and Unobserved Heterogeneity Consistent Partial Least Squares

Product Details

  • publication date: 05/05/2016
  • ISBN13: 9781483377445
  • Format: Paperback
  • Number Of Pages: 384
  • ID: 9781483377445
  • weight: 431
  • ISBN10: 148337744X
  • edition: 2nd Revised edition

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