A Comparison of Approaches for the Analysis of Interaction Effects Between Latent Variables Using Partial Least Squares Path Modeling

By Jörg Henseler, Wynne W. Chin. 2010

1,193 citations recorded by the source corpus.

Subfields: Information Systems and Management, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/7cc44ecbf182ca99a374dd693f50605969e52c4c

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Citations in the corpus

A Critical Examination of Common Beliefs About Partial Least Squares Path Modeling (2013, methodology): “In our review of other top research methods journals, we found one article about PLS (Henseler & Chin, 2010) published in Structural Equation Modeling and one article (Dijkstra, 1983) in Journal of Econometrics.”
Discovering Unobserved Heterogeneity in Structural Equation Models to Avert Validity Threats (2013, methodology): “Previous studies on PLS path modeling (e.g., Chin et al. 2003; Henseler and Chin 2010; Reinartz et al. 2009) first generated data by extracting latent variable scores to match the true relationships in the structural model and then generated data for the indicators by adding measurement errors to…”
Addressing Endogeneity in International Marketing Applications of Partial Least Squares Structural Equation Modeling (2018, methodology): “Moreover, in this studywe did not address how to dealwith endogeneity issues in PLS path models that include interaction terms, which are used, for example, in PLS-SEMbased moderator analyses (Hair et al. 2017; Henseler and Chin 2010).”
Partial least squares structural equation modeling in HRM research (2020, methodology): “However, when running a moderation analysis, researchers must carefully choose a suitable approach to compute the interaction term (Henseler & Chin, 2010) and employ bias-corrected and accelerated (BCa) confidence intervals when interpreting their results (Aguirre-Urreta & Rönkkö, in press).”
Using PLS path modeling in new technology research: updated guidelines (2016, background): “…interaction effects and quadratic effects can be easily analyzed by means of some rudimentary extensions to the standard PLS path modeling setup (Dijkstra and Henseler, 2011; Henseler and Fassott, 2010; Henseler et al., 2012; Henseler and Chin, 2010; Dijkstra and Schermelleh-Engel, 2014).”
ASSESSING REFLECTIVE MODELS IN MARKETING RESEARCH: A COMPARISON BETWEEN PLS AND PLSc ESTIMATES (2018, methodology): “…using Reflective-Composite Type or Reflective-Reflective Type (Ringle et al., 2012), mediation analysis (Nitzl et al., 2016), moderation analysis (Henseler & Chin 2010), multi-group Analysis (Henseler et al., 2016b; Sarstedt et al. 2011) and analysis with nonlinear effects (Djikstra & Henseler…”
Islamic tourism: an empirical examination of travel motivation and satisfaction in Malaysia (2017, methodology): “Analysis of the structural model and testing of hypotheses A two-stage approach was followed for evaluating the interaction effects of moderating variables modelled in PLS (Chin et al., 2003; Henseler & Chin, 2010; Sarkar et al., 2001; Walter et al., 2006).”
Proactive Environmental Strategy, Technological Eco-Innovation and Firm Performance—Case of Poland (2016, background): “firm size, pollution intensity and market internationalization) separately [69].”
PLS-SEM: Indeed a Silver Bullet (2011, background): “Other studies broach the issue of moderating effects (Henseler and Chin 2010; Henseler and Fassott 2010), hierarchical component models (Wetzels, Odekerken-Schroder, and van Oppen 2009), and higherorder interaction effects in hierarchical component models (Wilson 2010).”
An assessment of the use of partial least squares structural equation modeling in marketing research (2011, methodology): “... have been developed in recent years, including (1) confirmatory tetrad analysis for PLS-SEM to empirically test a construct’s measurement mode (Gudergan et al. 2008); (2) impact-performance matrix analysis (Slack 1994 ;V olckner et al. 2010); (3) response-based segmentation techniques, such as f”