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Partial Least Squares Path Modeling

  • Jörg Henseler
Chapter
Part of the International Series in Quantitative Marketing book series (ISQM)

Abstract

Structural equation modeling (SEM) is a family of statistical techniques that has become very popular in marketing. Its ability to model latent variables, to take various forms of measurement error into account, and to test entire theories makes it useful for a plethora of research questions. It does not come as a surprise that some of the most cited scholarly articles in the marketing domain are about SEM (e.g., Bagozzi and Yi 1988; Fornell and Larcker 1981), and that SEM is covered by two contributions within this volume. The need for two contributions arises from the SEM family tree having two major branches (Reinartz et al. 2009): covariance-based SEM (which is presented in Chap. 11) and variance-based SEM, which is presented in this chapter.

Notes

Acknowledgments

Major parts of this paper are taken from Henseler et al. (2016). The author acknowledges a financial interest in ADANCO and its distributor, Composite Modeling.

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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Design, Production and ManagementUniversity of TwenteEnschedeThe Netherlands

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