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Handbook of Partial Least Squares

Concepts, Methods and Applications

  • Book
  • © 2010

Overview

Editors:
  1. Vincenzo Esposito Vinzi

    1. Dept. Inf. Systems & Decision Sciences, ESSEC Business School of Paris, Cergy Pontoise CX, France

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  2. Wynne W. Chin

    1. Bauer College of Business, University of Houston, Houston, U.S.A.

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  3. Jörg Henseler

    1. Nijmegen School of Management, Radboud University, Nijmegen, Netherlands

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  4. Huiwen Wang

    1. School of Economics & Management, BeiHang University, Beijing, China, People's Republic

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  • Up-to-date review of the PLS methods recently developed and their applications in marketing
  • Complete and comprehensive overview of the field
  • Focus both on statistical methodology and selected real world problems
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Handbooks of Computational Statistics (SHCS)

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Table of contents (34 chapters)

  1. Front Matter

    Pages I-XIV
    Download chapter PDF

  2. Editorial: Perspectives on Partial Least Squares

    • Vincenzo Esposito Vinzi, Wynne W. Chin, Jörg Henseler, Huiwen Wang
    Pages 1-20

  3. Methods

    1. Front Matter

      Pages 22-22
      Download chapter PDF

  4. METHODS

    1. Latent Variables and Indices: Herman Wold’s Basic Design and Partial Least Squares

      • Theo K. Dijkstra
      Pages 23-46

    2. PLS Path Modeling: From Foundations to Recent Developments and Open Issues for Model Assessment and Improvement

      • Vincenzo Esposito Vinzi, Laura Trinchera, Silvano Amato
      Pages 47-82

    3. Bootstrap Cross-Validation Indices for PLS Path Model Assessment

      • Wynne W. Chin
      Pages 83-97

    4. A Bridge Between PLS Path Modeling and Multi-Block Data Analysis

      • Michel Tenenhaus, Mohamed Hanafi
      Pages 99-123

    5. Use of ULS-SEM and PLS-SEM to Measure a Group Effect in a Regression Model Relating Two Blocks of Binary Variables

      • Michel Tenenhaus, Emmanuelle Mauger, Christiane Guinot
      Pages 125-140

    6. A New Multiblock PLS Based Method to Estimate Causal Models: Application to the Post-Consumption Behavior in Tourism

      • Francisco Arteaga, Martina G. Gallarza, Irene Gil
      Pages 141-169

    7. An Introduction to a Permutation Based Procedure for Multi-Group PLS Analysis: Results of Tests of Differences on Simulated Data and a Cross Cultural Analysis of the Sourcing of Information System Services Between Germany and the USA

      • Wynne W. Chin, Jens Dibbern
      Pages 171-193

    8. Finite Mixture Partial Least Squares Analysis: Methodology and Numerical Examples

      • Christian M. Ringle, Sven Wende, Alexander Will
      Pages 195-218

    9. Prediction Oriented Classification in PLS Path Modeling

      • Silvia Squillacciotti
      Pages 219-233

    10. Conjoint Use of Variables Clustering and PLS Structural Equations Modeling

      • Valentina Stan, Gilbert Saporta
      Pages 235-246

    11. Design of PLS-Based Satisfaction Studies

      • Kai Kristensen, Jacob Eskildsen
      Pages 247-277

    12. A Case Study of a Customer Satisfaction Problem: Bootstrap and Imputation Techniques

      • Clara Cordeiro, Alexandra Machás, Maria Manuela Neves
      Pages 279-287

    13. Comparison of Likelihood and PLS Estimators for Structural Equation Modeling: A Simulation with Customer Satisfaction Data

      • Manuel J. Vilares, Maria H. Almeida, Pedro S. Coelho
      Pages 289-305

    14. Modeling Customer Satisfaction: A Comparative Performance Evaluation of Covariance Structure Analysis Versus Partial Least Squares

      • John Hulland, Michael J. Ryan, Robert K. Rayner
      Pages 307-325

    15. PLS in Data Mining and Data Integration

      • Svante Wold, Lennart Eriksson, Nouna Kettaneh
      Pages 327-357

    16. Three-Block Data Modeling by Endo- and Exo-LPLS Regression

      • Solve Sæbø, Magni Martens, Harald Martens
      Pages 359-379

    17. Regression Modelling Analysis on Compositional Data

      • Huiwen Wang, Jie Meng, Michel Tenenhaus
      Pages 381-406
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Keywords

About this book

Partial Least Squares is a family of regression based methods designed for the an- ysis of high dimensional data in a low-structure environment. Its origin lies in the sixties, seventies and eighties of the previous century, when Herman O. A. Wold vigorously pursued the creation and construction of models and methods for the social sciences, where “soft models and soft data” were the rule rather than the exception, and where approaches strongly oriented at prediction would be of great value. Theauthorwasfortunatetowitnessthedevelopment rsthandforafewyears. Herman Wold suggested (in 1977) to write a PhD-thesis on LISREL versus PLS in the context of latent variable models, more speci cally of “the basic design”. I was invited to his research team at the Wharton School, Philadelphia, in the fall of 1977. Herman Wold also honoured me by serving on my PhD-committee as a distinguished and decisive member. The thesis was nished in 1981. While I moved into another direction (speci cation, estimation and statistical inference in the c- text of model uncertainty) PLS sprouted very fruitfully in many directions, not only as regards theoretical extensions and innovations (multilevel, nonlinear extensions et cetera) but also as regards applications, notably in chemometrics, marketing, and political sciences. The PLS regression oriented methodology became part of main stream statistical analysis, as can be gathered from references and discussions in important books and journals. See e. g. Hastie et al. (2001), or Stone and Brooks (1990),Frank and Friedman (1993),Tenenhauset al. (2005),there are manyothers.

Reviews

From the reviews:

“I found the book to be a good resource for those without prior knowledge of PLS looking forward to an introduction as well as a comprehensive reference for every researcher and every practitioner interested in the most recent advances in PLS methodology. All of them should have this title as an essential part of their library. … Great Stuff! … will be the definitive reference work in the field for a good time to come. … it is wonderfully readable and referable.” (Current Engineering Practice, August, 2011)

“The book is divided into three parts, dealing, respectively, with contemporary methodological developments, applications in marketing and related areas, and tutorials on particular aspects of PLS analysis. It provides a comprehensive overview of recent advances in the area, and describes cutting-edge methodological developments showing how PLS can be applied in tackling a wide variety of problem types. … for people who do have some prior experience with PLS, this book is a goldmine of novel methodological and practical applications.” (David J. Hand, International Statistical Review, Vol. 80 (3), 2012)

Editors and Affiliations

  • Dept. Inf. Systems & Decision Sciences, ESSEC Business School of Paris, Cergy Pontoise CX, France

    Vincenzo Esposito Vinzi

  • Bauer College of Business, University of Houston, Houston, U.S.A.

    Wynne W. Chin

  • Nijmegen School of Management, Radboud University, Nijmegen, Netherlands

    Jörg Henseler

  • School of Economics & Management, BeiHang University, Beijing, China, People's Republic

    Huiwen Wang

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