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Handbook of Partial Least Squares: Concepts, Methods and Applications

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TLDR
The "Handbook of Partial Least Squares (PLS) and Marketing: Concepts, Methods and Applications" is the second volume in the series of the Handbooks of Computational Statistics as mentioned in this paper.
Abstract
The "Handbook of Partial Least Squares (PLS) and Marketing: Concepts, Methods and Applications" is the second volume in the series of the Handbooks of Computational Statistics. This Handbook represents a comprehensive overview of PLS methods with specific reference to their use in Marketing and with a discussion of the directions of current research and perspectives. The Handbook covers the broad area of PLS Methods from Regression to Structural Equation Modeling, from methods to applications, from software to interpretation of results. The Handbook features papers on the use and the analysis of latent variables and indicators by means of the PLS Path Modeling approach from the design of the causal network to the model assessment and improvement. Moreover, within the PLS framework, the Handbook addresses, among others, special and advanced topics such as the analysis of multi-block, multi-group and multi-structured data, the use of categorical indicators, the study of interaction effects, the integration of classification issues, the validation aspects and the comparison between thecomponent-basedPLS approach and the covariance-based Structural Equation Modeling. Most chapters comprise a thorough discussion of applications to problems from Marketing and related areas. Furthermore, a few tutorials focus on some key aspects of PLS analysis with a didactic approach. This Handbook serves as both an introduction for those without prior knowledge of PLS as well as a comprehensive reference for researchers and practitioners interested in the most recent advances in PLS methodology.

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Journal ArticleDOI

A new criterion for assessing discriminant validity in variance-based structural equation modeling

TL;DR: In this paper, the heterotrait-monotrait ratio of correlations is used to assess discriminant validity in variance-based structural equation modeling. But it does not reliably detect the lack of validity in common research situations.
Posted Content

The Use of Partial Least Squares Path Modeling in International Marketing

TL;DR: An evaluation of double-blind reviewed journals through important academic publishing databases revealed that more than 30 academic articles in the domain of international marketing (in a broad sense) used PLS path modeling as means of statistical analysis.
Journal ArticleDOI

Using PLS path modeling in new technology research: updated guidelines

TL;DR: This paper presents new developments, such as consistent PLS, confirmatory composite analysis, and the heterotrait-monotrait ratio of correlations, and updated guidelines of how to use PLS and how to report and interpret its results.
Journal ArticleDOI

Common Beliefs and Reality About PLS: Comments on Rönkkö and Evermann (2013)

TL;DR: In this article, the authors address Ronkko and Evermann's criticisms of the Partial Least Squares (PLS) approach to structural equation modeling and conclude that PLS should continue to be used as an important statistical tool for management and organizational research, as well as other social science disciplines.
Book ChapterDOI

Partial Least Squares Structural Equation Modeling

TL;DR: Partial least squares structural equation modeling (PLS-SEM) has become a popular method for estimating path models with latent variables and their relationships as discussed by the authors, and a common goal of PLSSEM analyses is to identify key success factors and sources of competitive advantage for important target constructs such as customer satisfaction, customer loyalty, behavioral intentions, and user behavior.
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