Partial Least Squares Path Modeling

Part I. Basic Concepts and Extensions

1. Partial Least Squares: The Gestation Period
Richard Noonan

2. Partial Least Squares Path Modeling: Updated Guidelines
Jörg Henseler, Geoffrey Hubona, Pauline Ash Ray

3. Going Beyond Composites: Conducting a Factor-Based PLS-SEM Analysis
Ned Kock

4. A Perfect Match Between a Model and a Mode
Theo K. Dijkstra

5. Quantile Composite-Based Model: A Recent Advance in PLS-PM
Cristina Davino, Pasquale Dolce, Stefania Taralli

6. Ordinal Consistent Partial Least Squares
Florian Schuberth, Gabriele Cantaluppi

Part II. Methodological Issues

7. Predictive Path Modeling Through PLS and Other Component-Based Approaches: Methodological Issues and Performance Evaluation
Pasquale Dolce, Vincenzo Esposito Vinzi, Carlo Lauro

8. Mediation Analyses in Partial Least Squares Structural Equation Modeling: Guidelines and Empirical Examples
Gabriel Cepeda Carrión, Christian Nitzl, José L. Roldán

9. Treating Unobserved Heterogeneity in PLS-SEM: A Multi-method Approach
Marko Sarstedt, Christian M. Ringle, Joseph F. Hair

10. Applying Multigroup Analysis in PLS-SEM: A Step-by-Step Process
Lucy Matthews

11. Common Method Bias: A Full Collinearity Assessment Method for PLS-SEM
Ned Kock

12. Integrating Non-metric Data in Partial Least Squares Path Models: Methods and Application
Francesca Petrarca, Giorgio Russolillo, Laura Trinchera

13. Model Misspecifications and Bootstrap Parameter Recovery in PLS-SEM and CBSEM-Based Exploratory Modeling
Pratyush N. Sharma, Ryan T. Pohlig, Kevin H. Kim

Part III. Applications

14. Personality, Intellectual Ability, and the Self-Concept of Gifted Children: An Application of PLS-SEM
R. Frank Falk

15. Ethical Awareness, Ethical Judgment, and Whistleblowing: A Moderated Mediation Analysis
Hengky Latan, Charbel Jose Chiappetta Jabbour, Ana Beatriz Lopes Sousa Jabbour

16. Latent Variable Regression for Laboratory Hyperspectral Images
Paul Geladi, Hans Grahn, Kim Esbensen

17. Dealing with Nonlinearity in Importance-Performance Map Analysis (IPMA): An Integrative Framework in a PLS-SEM Context
Sandra Streukens, Sara Leroi-Werelds, Kim Willems

Avainsanat: Statistics, Statistical Theory and Methods, Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law, Statistics for Business/Economics/Mathematical Finance/Insurance, Statistics and Computing/Statistics Programs, Econometrics, Psychometrics