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Latent class analysis in PLS-SEM: A review and recommendations for future applications

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  • Sarstedt, Marko
  • Radomir, Lăcrămioara
  • Moisescu, Ovidiu Ioan
  • Ringle, Christian M.

Abstract

With the increasing prominence of partial least squares structural equation modeling (PLS-SEM) in business research, the use of latent class analyses for identifying and treating unobserved heterogeneity has also gained momentum. Researchers have introduced various latent class approaches in a PLS-SEM context, of which finite mixture PLS (FIMIX-PLS) plays a central role due to its ability to identify heterogeneity and indicate a suitable number of segments to extract from the data. However, applying FIMIX-PLS requires researchers to make several choices that, if incorrect, could lead to wrong results and false conclusions. Addressing this concern, we present the results of a systematic review of FIMIX-PLS applications published in major business research journals. Our review provides an overview of the interdependencies between researchers’ choices and identifies potential problem areas. Based on our results, we offer concrete guidance on how to prevent common pitfalls when using FIMIX-PLS, and identify future research areas.

Suggested Citation

  • Sarstedt, Marko & Radomir, Lăcrămioara & Moisescu, Ovidiu Ioan & Ringle, Christian M., 2022. "Latent class analysis in PLS-SEM: A review and recommendations for future applications," Journal of Business Research, Elsevier, vol. 138(C), pages 398-407.
  • Handle: RePEc:eee:jbrese:v:138:y:2022:i:c:p:398-407
    DOI: 10.1016/j.jbusres.2021.08.051
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    1. Ringle, Christian M. & Sarstedt, Marko & Schlittgen, Rainer & Taylor, Charles R., 2013. "PLS path modeling and evolutionary segmentation," Journal of Business Research, Elsevier, vol. 66(9), pages 1318-1324.
    2. N. Thamaraiselvan & P. Sridevi & B. Senthil Arasu & Thushara Srinivasan, 2018. "Evaluation of employee brand using typological analysis in Indian airline organisation," International Journal of Business Excellence, Inderscience Enterprises Ltd, vol. 16(4), pages 478-496.
    3. Vermunt, Jeroen K., 2010. "Latent Class Modeling with Covariates: Two Improved Three-Step Approaches," Political Analysis, Cambridge University Press, vol. 18(4), pages 450-469.
    4. Marko Sarstedt & Christian M. Ringle & Joseph F. Hair, 2022. "Partial Least Squares Structural Equation Modeling," Springer Books, in: Christian Homburg & Martin Klarmann & Arnd Vomberg (ed.), Handbook of Market Research, pages 587-632, Springer.
    5. Marko Sarstedt & Christian Ringle, 2010. "Treating unobserved heterogeneity in PLS path modeling: a comparison of FIMIX-PLS with different data analysis strategies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(8), pages 1299-1318.
    6. Carsten Hahn & Michael D. Johnson & Andreas Herrmann & Frank Huber, 2002. "Capturing Customer Heterogeneity Using A Finite Mixture Pls Approach," Schmalenbach Business Review (sbr), LMU Munich School of Management, vol. 54(3), pages 243-269, July.
    7. Venkatram Ramaswamy & Wayne S. Desarbo & David J. Reibstein & William T. Robinson, 1993. "An Empirical Pooling Approach for Estimating Marketing Mix Elasticities with PIMS Data," Marketing Science, INFORMS, vol. 12(1), pages 103-124.
    8. Jan-Michael Becker & Christian Ringle & Marko Sarstedt & Franziska Völckner, 2015. "How collinearity affects mixture regression results," Marketing Letters, Springer, vol. 26(4), pages 643-659, December.
    9. Karl Widerquist, 2018. "The Bottom Line," Exploring the Basic Income Guarantee, in: A Critical Analysis of Basic Income Experiments for Researchers, Policymakers, and Citizens, chapter 0, pages 93-98, Palgrave Macmillan.
    10. Schlittgen, Rainer & Ringle, Christian M. & Sarstedt, Marko & Becker, Jan-Michael, 2016. "Segmentation of PLS path models by iterative reweighted regressions," Journal of Business Research, Elsevier, vol. 69(10), pages 4583-4592.
    11. Marko Sarstedt & Jan-Michael Becker & Christian M. Ringle & Manfred Schwaiger, 2011. "Uncovering and Treating Unobserved Heterogeneity with FIMIX-PLS: Which Model Selection Criterion Provides an Appropriate Number of Segments?," Schmalenbach Business Review (sbr), LMU Munich School of Management, vol. 63(1), pages 34-62, January.
    12. Fordellone, Mario & Vichi, Maurizio, 2020. "Finding groups in structural equation modeling through the partial least squares algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 147(C).
    13. Bolck, Annabel & Croon, Marcel & Hagenaars, Jacques, 2004. "Estimating Latent Structure Models with Categorical Variables: One-Step Versus Three-Step Estimators," Political Analysis, Cambridge University Press, vol. 12(1), pages 3-27, January.
    14. Sarstedt, Marko & Hair, Joseph F. & Ringle, Christian M. & Thiele, Kai O. & Gudergan, Siegfried P., 2016. "Estimation issues with PLS and CBSEM: Where the bias lies!," Journal of Business Research, Elsevier, vol. 69(10), pages 3998-4010.
    15. Marko Sarstedt & Christian M Ringle & Jun-Hwa Cheah & Hiram Ting & Ovidiu I Moisescu & Lacramioara Radomir, 2020. "Structural model robustness checks in PLS-SEM," Tourism Economics, , vol. 26(4), pages 531-554, June.
    16. V. Esposito Vinzi & L. Trinchera & S. Squillacciotti & M. Tenenhaus, 2008. "REBUS‐PLS: A response‐based procedure for detecting unit segments in PLS path modelling," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 439-458, September.
    17. Sawa, Takamitsu, 1978. "Information Criteria for Discriminating among Alternative Regression Models," Econometrica, Econometric Society, vol. 46(6), pages 1273-1291, November.
    18. Rigdon, Edward E., 2016. "Choosing PLS path modeling as analytical method in European management research: A realist perspective," European Management Journal, Elsevier, vol. 34(6), pages 598-605.
    19. Sarstedt, Marko & Hair, Joseph F. & Cheah, Jun-Hwa & Becker, Jan-Michael & Ringle, Christian M., 2019. "How to specify, estimate, and validate higher-order constructs in PLS-SEM," Australasian marketing journal, Elsevier, vol. 27(3), pages 197-211.
    20. Rainer Schlittgen, 2011. "A weighted least-squares approach to clusterwise regression," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(2), pages 205-217, June.
    21. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    22. Kamel Jedidi & Harsharanjeet S. Jagpal & Wayne S. DeSarbo, 1997. "Finite-Mixture Structural Equation Models for Response-Based Segmentation and Unobserved Heterogeneity," Marketing Science, INFORMS, vol. 16(1), pages 39-59.
    23. Wayne S. DeSarbo & C. Anthony Di Benedetto & Kamel Jedidi & Michael Song, 2006. "Identifying Sources of Heterogeneity for Empirically Deriving Strategic Types: A Constrained Finite-Mixture Structural-Equation Methodology," Management Science, INFORMS, vol. 52(6), pages 909-924, June.
    24. Necmi K. Avkiran & Christian M. Ringle (ed.), 2018. "Partial Least Squares Structural Equation Modeling," International Series in Operations Research and Management Science, Springer, number 978-3-319-71691-6, December.
    25. Necmi Kemal Avkiran, 2018. "An in-depth discussion and illustration of partial least squares structural equation modeling in health care," Health Care Management Science, Springer, vol. 21(3), pages 401-408, September.
    26. Marko Sarstedt & Jun-Hwa Cheah, 2019. "Partial least squares structural equation modeling using SmartPLS: a software review," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 196-202, September.
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