Tips to use partial least squares structural equation modelling (PLS-SEM) in knowledge management

By Gabriel Cepeda Carrion, Juan Gabriel Cegarra-Navarro, Valentina Cillo. Journal of Knowledge Management, 2019

532 citations recorded by the source corpus.

PurposeStructural equation modelling (SEM) has been defined as the combination of latent variables and structural relationships. The partial least squares SEM (PLS-SEM) is used to estimate complex cause-effect relationship models with latent variables as the most salient research methods across a variety of disciplines, including knowledge management (KM). Following the path initiated by different domains in business research, this paper aims to examine how PLS-SEM has been applied in KM research, also providing some new guidelines how to improve PLS-SEM report analysis.Design/methodology/approachTo ensure an objective way to analyse relevant works in the field of KM, this study conducted a systematic literature review of 63 publications in three SSCI-indexed and specific KM journals between 2015 and 2017.FindingsOur results show that over the past three years, a significant amount of KM works has empirically used PLS-SEM. The findings also suggest that in light of recent developments of PLS-SEM reporting, some common misconceptions among KM researchers occurred mainly related to the reasons for using PLS-SEM, the purposes of PLS-SEM analysis, data characteristics, model characteristics and the evaluation of the structural models.Originality/valueThis study contributes to that vast KM literature by documenting the PLS-SEM-related problems and misconceptions. Therefore, it will shed light for better reports in PLS-SEM studies in the KM field.

Subfields: Artificial Intelligence, Information Systems and Management, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/a462fd2cc87d73fa1762404d99aeab24775b50a1

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Citations in the corpus

Structural model robustness checks in PLS-SEM (2020, methodology): “Similarly, the application of latent class techniques such as FIMIX-PLS is scarce, not only in tourism but also in other fields of business research (Ali et al., 2018b; Cepeda Carrión and Cegarra, 2019; Ringle et al., 2019).”