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  4. An assessment of the use of partial least squares structural equation modeling in marketing research
 
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An assessment of the use of partial least squares structural equation modeling in marketing research

Publikationstyp
Journal Article
Date Issued
2012-05-01
Sprache
English
Author(s)
Hair, Joseph F.  
Sarstedt, Marko  
Ringle, Christian M.  orcid-logo
Mena, Jeannette A.  
Institut
Personalwirtschaft und Arbeitsorganisation W-9  
TORE-URI
http://hdl.handle.net/11420/4043
Journal
Journal of the Academy of Marketing Science  
Volume
40
Issue
3
Start Page
414
End Page
433
Citation
Journal of the Academy of Marketing Science 40 (3): 414-433 (2012-05-01)
Publisher DOI
10.1007/s11747-011-0261-6
Scopus ID
2-s2.0-80053611303
Most methodological fields undertake regular critical reflections to ensure rigorous research and publication practices, and, consequently, acceptance in their domain. Interestingly, relatively little attention has been paid to assessing the use of partial least squares structural equation modeling (PLS-SEM) in marketing research-despite its increasing popularity in recent years. To fill this gap, we conducted an extensive search in the 30 top ranked marketing journals that allowed us to identify 204 PLS-SEM applications published in a 30-year period (1981 to 2010). A critical analysis of these articles addresses, amongst others, the following key methodological issues: reasons for using PLS-SEM, data and model characteristics, outer and inner model evaluations, and reporting. We also give an overview of the interdependencies between researchers' choices, identify potential problem areas, and discuss their implications. On the basis of our findings, we provide comprehensive guidelines to aid researchers in avoiding common pitfalls in PLS-SEM use. This study is important for researchers and practitioners, as PLS-SEM requires several critical choices that, if not made correctly, can lead to improper findings, interpretations, and conclusions.
Subjects
Empirical research methods
Partial least squares
Path modeling
Structural equation modeling
DDC Class
000: Allgemeines, Wissenschaft
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