Int. Journal of Business Science and Applied Management, Volume 6, Issue 2, 2011

Book Review: Handbook of Partial Least Squares:

Concepts, Methods and Applications

Ken Kwong-Kay Wong

Universitas 21 Global

5 Shenton Way, #01-01 UIC Building, Singapore, 068808

Tel: +1 (416) 892-9664

E-mail: kwong@u21global.edu.sg

Book Information

Book Title: Handbook of Partial Least Squares: Concepts, Methods and Applications

Author: Esposito Vinzi, V.; Chin, W.W.; Henseler, J.; Wang, H.

Publisher: Springer

Edition: 1st edition

Year: 2010

Pages: 798 pages

ISBN: 978-3540328254

Price: £224.00

Keywords: statistics, partial least squares, marketing, structural equation modelling

Ken Kwong-Kay Wong

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BOOK REVIEW

Business and management researchers would probably agree that some applied research projects

have limited participants because of the project nature. Surveying multinational CEOs, female senior

executives, or physically disabled workers can be challenging because the sample size can be small and

the data distribution is often skewed. These problems may cause researchers to draw incorrect

inference and prevent them from carrying out structural equation modeling (SEM) where strict data

assumptions are required.

Partial Least Squares (PLS) is a soft-modeling approach developed by Herman Wold in the mid

60s. Since PLS is insensitive to data non-normality, with no parameter identification problem, and has

relatively small sample size requirement, it is often considered by researchers to be a good alternative

to traditional covariance-based approach in SEM.

The first edition of the Handbook of Partial Least Squares was just published by Springer in

February 2010, after a 3-year publication delay. This 800-page book is the second volume in the

Springer Handbooks of Computational Statistics series. It is positioned to be a comprehensive reference

guide that explores the concepts, methods, and applications of the PLS statistical procedure. The book

is written for professors, PhD students, and research professionals who want to gain a better

understanding of this emerging multivariate analysis approach. Since it assumes some knowledge of

intermediate statistical knowledge, this book is not a beginner text for college students. The global

research community would benefit from this handbook due to a general lack of PLS publication in the

market. This book is timely as PLS has gained increasing attention of the research community in the

past decade.

This handbook is edited by V. Esposito Vinzi et al. who are renowned experts in the PLS field. A

whopping 33 articles are contributed by 74 authors from the global academic and research community.

There are three main parts to the handbook, which one should read in sequence from the book's

beginning to end.

The first part explores the PLS methodology in general. The articles are grouped into five sections

to help readers understand PLS in a step-by-step manner. The first section (Chapter 1-3) consists of

three articles, discussing the basic concept and model assessment of PLS. I enjoy reading Dijkstra's

article the most because he reveals the history of PLS from a first hand perspective. As Wold's PhD

student at the Wharton School, he brings readers back in time to view the early development of PLS

vividly. Dijkstra clearly explains the "basic design" and how PLS can be used to construct proxies for

the latent variables. The second section (Chapter 4-7) extends the PLS Path Modeling discussion to

help readers design advanced, multi-block models. I find Chin and Dibbern's article interesting as they

present a new permutation-based procedure for carrying out multi-group PLS analysis. The issue of

classification is being covered in the third section (Chapter 8-10), while the fourth section (Chapter 11-

14) illustrates how PLS path modeling can be used in customer satisfaction studies. Advanced PLS

regression modeling is explored in the fifth section (Chapter 15-17). Readers may find the paper by

Wold, Eriksson and Kettaneh useful as it explores the use of PLS in data mining and data integration.

Part two (Chapter 18 to 27) is my favourite as it shows how PLS can be applied to solve

marketing problems. It covers case studies ranging from employee satisfaction, brand preference,

customer loyalty, customer value, web strategy, to total quality management. I believe business and

management researchers will appreciate the various examples presented in the book. PLS is presented

as a good alternative to traditional AMOS or LISREL approach in conducting SEM analysis if the

model is designed properly. Kristensen and Eskildsen's article "Design of PLS-Based Satisfaction

Studies" is a must read for marketers who want to make use of PLS in their customer satisfaction

projects.

The final part of this book (Chapter 28 to 33) is designed to be a tutorial for PLS learners. It is a

collection of "how to" articles, guiding readers to properly design and build PLS models. I enjoy

reading Chin's article "How to Write Up and Report PLS Analyses" as it helps readers to report their

research findings in a professional manner.

While this book serves as a great resource to those who are new to PLS, researchers who have

been actively using this statistical procedure and following its development since the late 90s may find

it a slight disappointment. This is because the book mainly consists of extended version of existing PLS

literature that has been published in the past decade. Another imperfection can be found in the tutorial

section. While the articles in part three help readers to choose the right software and develop advanced

model for PLS analysis, the book lacks sufficient guidelines to alert readers what "not to do" when

using PLS in their research projects. As MIS Quarterly (MISQ) has twice pointed out in its editorial

(Marcoulides & Saunders, 2006; Marcoulides, Chin & Saunders, 2009), PLS is not a magical silver

Int. Journal of Business Science and Applied Management / Business-and-Management.org

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bullet for all kinds of research projects. Researchers must pay attention to its limitations and

restrictions. These important messages seem to be lacking from this otherwise great handbook of PLS.

With a suggested retail price of £224.00, the Handbook of Partial Least Squares is certainly not an

impulse purchase for most readers. If you are a professor or researcher who wants to gain insights into

this statistical procedure to tackle problematic data set, this book is a good buy considering the

enormous effort the editors have put in to bring this book to life. For those who want to take a peek of

this masterpiece, you will be pleased to learn that Google Books has a copy for your preview.

REFERENCES

Marcoulides G.A. and Saunders, C. (2006). PLS: A Silver Bullet? MIS Quarterly. 30(2), pp. iii-ix.

Retrieved from: http://www.misq.org/archivist/vol/no30/issue2/EdCommentsV30N2.pdf

Marcoulides, G.A., Chin, W.W., & Saunders, C. (2009). A Critical Look at Partial Least Squares

Modeling. MIS Quarterly. 33(1), pp. 171-175. Retrieved from:

http://www.misq.org/archivist/vol/no33/issue1/ForewordPLS.pdf