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PLS FAC-SEM: an illustrated step-by-step guideline to obtain a unique insight in factorial data

Sandra Streukens (Department of Marketing and Strategy, Hasselt University, Hasselt, Belgium )
Sara Leroi-Werelds (Department of Marketing and Strategy, Hasselt University, Hasselt, Belgium )

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 17 October 2016

Abstract

Purpose

The purpose of this paper is to provide an illustrated step-by-step guideline of the partial least squares factorial structural equation modeling (PLS FAC-SEM) approach. This approach allows researchers to assess whether and how model relationships vary as a function of an underlying factorial design, both in terms of the design factors in isolation (i.e. main effects) as well as their joint impact (i.e. interaction effects).

Design/methodology/approach

After an introduction of its building blocks as well as a comparison with related methods (i.e. n-way analysis of variance (ANOVA) and multi-group analysis (MGA)), a step-by-step guideline of the PLS FAC-SEM approach is presented. Each of the steps involved in the PLS FAC-SEM approach is illustrated using data from a customer value study.

Findings

On a methodological level, the key result of this research is the presentation of a generally applicable step-by-step guideline of the PLS FAC-SEM approach. On a context-specific level, the findings demonstrate how the predictive ability of several key customer value measurement methods depends on the type of offering (feel-think), the level of customer involvement (low-high), and their interaction (feel-think offerings×low-high involvement).

Originality/value

This is a first attempt to apply the factorial structural equation models (FAC-SEM) approach in a PLS-SEM context. Consistent with the general differences between PLS-SEM and covariance-based structural equation modeling (CB-SEM), the FAC-SEM approach, which was originally developed for CB-SEM, therefore becomes available for a larger amount of and different types of research situations.

Keywords

Acknowledgements

The data collection was supported by the Marketing Science Institute. The study was conducted in the period that the second author received an FWO scholarship.

Citation

Streukens, S. and Leroi-Werelds, S. (2016), "PLS FAC-SEM: an illustrated step-by-step guideline to obtain a unique insight in factorial data", Industrial Management & Data Systems, Vol. 116 No. 9, pp. 1922-1945. https://doi.org/10.1108/IMDS-07-2015-0318

Publisher

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Emerald Group Publishing Limited

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