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Partial Least Squares Structural Equation Modeling

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Handbook of Market Research

Abstract

Partial least squares structural equation modeling (PLS-SEM) has become a popular method for estimating path models with latent variables and their relationships. A common goal of PLS-SEM 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. Building on an introduction of the fundamentals of measurement and structural theory, this chapter explains how to specify and estimate path models using PLS-SEM. Complementing the introduction of the PLS-SEM method and the description of how to evaluate analysis results, the chapter also offers an overview of complementary analytical techniques. A PLS-SEM application of the widely recognized corporate reputation model illustrates the method.

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Acknowledgments

This chapter uses the statistical software SmartPLS 3 (https://www.smartpls.com). Ringle acknowledges a financial interest in SmartPLS.

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Authors and Affiliations

  1. Faculty of Economics and Management, Otto-von-Guericke University Magdeburg, Magdeburg, Germany

    Marko Sarstedt

  2. Faculty of Economics and Business Administration, Babeș-Bolyai-University, Cluj, Romania

    Marko Sarstedt

  3. Institute of Human Resource Management and Organizations (HRMO), Hamburg University of Technology (TUHH), Hamburg, Germany

    Christian M. Ringle

  4. Waikato Management School, University of Waikato, Hamilton, New Zealand

    Christian M. Ringle

  5. Cleverdon Chair of Business, Mitchell College of Business, University of South Alabama, Mobile, AL, USA

    Joseph F. Hair

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    Christian Homburg

  2. Inst. Informations Systems and Marketing Marketing & Sales Research Group, Karlsruher Institut für Technologie, Karlsruhe, Germany

    Martin Klarmann

  3. Faculty of Economics and Business, University of Groningen, Groningen, The Netherlands

    Arnd E. Vomberg

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  1. University of Mannheim, Mannheim, Germany

    Christian Homburg

  2. Karlsruhe Institute of Technology, Karlsruhe, Germany

    Martin Klarmann

  3. University of Groningen, Groningen, Niederlande

    Arnd Vomberg

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Sarstedt, M., Ringle, C.M., Hair, J.F. (2021). Partial Least Squares Structural Equation Modeling. In: Homburg, C., Klarmann, M., Vomberg, A.E. (eds) Handbook of Market Research. Springer, Cham. https://doi.org/10.1007/978-3-319-05542-8_15-2

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    Partial Least Squares Structural Equation Modeling
    Published:
    22 July 2021

    DOI: https://doi.org/10.1007/978-3-319-05542-8_15-2

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    Partial Least Squares Structural Equation Modeling
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    22 August 2017

    DOI: https://doi.org/10.1007/978-3-319-05542-8_15-1

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