Treating unobserved heterogeneity in PLS path modeling: a comparison of FIMIX-PLS with different data analysis strategies

DOI10.1080/02664760903030213OpenAlexW2122700558WikidataQ61456734 ScholiaQ61456734MaRDI QIDQ5123614

Christian M. Ringle, Marko Sarstedt

Publication date: 29 September 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664760903030213

zbMATH Keywords

heterogeneitylatent classmarket segmentationfinite mixturepath modelingcorporate reputationpartial least square (PLS)

Mathematics Subject Classification ID

Statistics (62-XX)

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Uses Software

• Mplus
• SmartPLS

Cites Work

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• On the convergence of the partial least squares path modeling algorithm
• STEMM: A general finite mixture structural equation model
• Coefficient alpha and the internal structure of tests
• Finite mixture and Markov switching models.
• Some recent research in the analysis of mixture distributions
• REBUS‐PLS: A response‐based procedure for detecting unit segments in PLS path modelling