Abstract
Purpose The authors aim to present partial least squares (PLS) as an evolving approach to structural equation modeling (SEM), highlight its advantages and limitations and provide an overview of recent research on the method across various fields.
Design/methodology/approach In this review article, the authors merge literatures from the marketing, management, and management information systems fields to present the state-of-the art of PLS-SEM research. Furthermore, the authors meta-analyze recent review studies to shed light on popular reasons for PLS-SEM usage.
Findings PLS-SEM has experienced increasing dissemination in a variety of fields in recent years with nonnormal data, small sample sizes and the use of formative indicators being the most prominent reasons for its application. Recent methodological research has extended PLS-SEM's methodological toolbox to accommodate more complex model structures or handle data inadequacies such as heterogeneity.
Research limitations/implications While research on the PLS-SEM method has gained momentum during the last decade, there are ample research opportunities on subjects such as mediation or multigroup analysis, which warrant further attention.
Originality/value This article provides an introduction to PLS-SEM for researchers that have not yet been exposed to the method. The article is the first to meta-analyze reasons for PLS-SEM usage across the marketing, management, and management information systems fields. The cross-disciplinary review of recent research on the PLS-SEM method also makes this article useful for researchers interested in advanced concepts.
Item Type: | Journal article |
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Keywords: | Structural equation modeling, partial least squares, PLS-SEM |
Faculties: | Munich School of Management > Institute for Marketing |
Subjects: | 300 Social sciences > 330 Economics |
ISSN: | 18778585 |
Language: | English |
Item ID: | 96161 |
Date Deposited: | 09. May 2023, 06:37 |
Last Modified: | 09. May 2023, 06:37 |