Segmentation of PLS path models by iterative reweighted regressions

Rainer Schlittgen; Marko Sarstedt; Christian M. Ringle; Jan-Michael Becker

doi:10.3990/2.344

Segmentation of PLS path models by iterative reweighted regressions

Rainer Schlittgen, Marko Sarstedt, Christian M. Ringle, Jan-Michael Becker

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

Uncovering unobserved heterogeneity is a requirement to obtain valid results when using the structural equation modeling (SEM) method with empirical data. Conventional segmentation methods usually fail in SEM since they account for the observations but not the latent variables and their relationships in the structural model. This research introduces a new segmentation approach to variancebased SEM. The iterative reweighted regressions segmentation method for PLS (PLS-IRRS) effectively identifies segments in data sets. In comparison with existing alternatives, PLS-IRRS is multiple times faster while delivering the same quality of results. We believe that PLS-IRRS has the potential to become one of the primary choices to address the critical issue of unobserved heterogeneity in PLS-SEM.

Original language	English
Title of host publication	Proceedings of the 2nd International Symposium on Partial Least Squares Path Modeling
Subtitle of host publication	The Conference for PLS Users
Editors	Jörg Henseler, Christian Ringle, José Roldán, Gabriel Cepeda
Place of Publication	Enschede
Publisher	University of Twente
Number of pages	12
ISBN (Print)	9789036540568
DOIs	https://doi.org/10.3990/2.344
Publication status	Published - 2015
Externally published	Yes
Event	2015 PLS User Conference: 2nd International Symposium on Partial Least Squares Path Modeling - The Conference for PLS Users - Seville, Spain Duration: 16 Jun 2015 → 19 Jun 2015

Conference

Conference	2015 PLS User Conference
Country/Territory	Spain
City	Seville
Period	16/06/15 → 19/06/15

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10.3990/2.344

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Proceedings of the 2nd International Symposium on Partial Least Squares Path Modeling: The Conference for PLS Users
Henseler, J., Ringle, C., Roldán, J. & Cepeda, G., 2015, Enschede: University of Twente. 414 p.
Research output: Book/Report › Book editing › Popular

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Schlittgen, Rainer ; Sarstedt, Marko ; Ringle, Christian M. et al. / Segmentation of PLS path models by iterative reweighted regressions. Proceedings of the 2nd International Symposium on Partial Least Squares Path Modeling: The Conference for PLS Users. editor / Jörg Henseler ; Christian Ringle ; José Roldán ; Gabriel Cepeda. Enschede : University of Twente, 2015.

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title = "Segmentation of PLS path models by iterative reweighted regressions",

abstract = "Uncovering unobserved heterogeneity is a requirement to obtain valid results when using the structural equation modeling (SEM) method with empirical data. Conventional segmentation methods usually fail in SEM since they account for the observations but not the latent variables and their relationships in the structural model. This research introduces a new segmentation approach to variancebased SEM. The iterative reweighted regressions segmentation method for PLS (PLS-IRRS) effectively identifies segments in data sets. In comparison with existing alternatives, PLS-IRRS is multiple times faster while delivering the same quality of results. We believe that PLS-IRRS has the potential to become one of the primary choices to address the critical issue of unobserved heterogeneity in PLS-SEM.",

author = "Rainer Schlittgen and Marko Sarstedt and Ringle, {Christian M.} and Jan-Michael Becker",

year = "2015",

doi = "10.3990/2.344",

language = "English",

isbn = "9789036540568",

editor = "J{\"o}rg Henseler and Christian Ringle and Jos{\'e} Rold{\'a}n and Gabriel Cepeda",

booktitle = "Proceedings of the 2nd International Symposium on Partial Least Squares Path Modeling",

publisher = "University of Twente",

address = "Netherlands",

note = "2015 PLS User Conference : 2nd International Symposium on Partial Least Squares Path Modeling - The Conference for PLS Users ; Conference date: 16-06-2015 Through 19-06-2015",

}

Schlittgen, R, Sarstedt, M, Ringle, CM & Becker, J-M 2015, Segmentation of PLS path models by iterative reweighted regressions. in J Henseler, C Ringle, J Roldán & G Cepeda (eds), Proceedings of the 2nd International Symposium on Partial Least Squares Path Modeling: The Conference for PLS Users. University of Twente, Enschede, 2015 PLS User Conference, Seville, Spain, 16/06/15. https://doi.org/10.3990/2.344

Segmentation of PLS path models by iterative reweighted regressions. / Schlittgen, Rainer; Sarstedt, Marko; Ringle, Christian M. et al.
Proceedings of the 2nd International Symposium on Partial Least Squares Path Modeling: The Conference for PLS Users. ed. / Jörg Henseler; Christian Ringle; José Roldán; Gabriel Cepeda. Enschede: University of Twente, 2015.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Segmentation of PLS path models by iterative reweighted regressions

AU - Schlittgen, Rainer

AU - Sarstedt, Marko

AU - Ringle, Christian M.

AU - Becker, Jan-Michael

PY - 2015

Y1 - 2015

N2 - Uncovering unobserved heterogeneity is a requirement to obtain valid results when using the structural equation modeling (SEM) method with empirical data. Conventional segmentation methods usually fail in SEM since they account for the observations but not the latent variables and their relationships in the structural model. This research introduces a new segmentation approach to variancebased SEM. The iterative reweighted regressions segmentation method for PLS (PLS-IRRS) effectively identifies segments in data sets. In comparison with existing alternatives, PLS-IRRS is multiple times faster while delivering the same quality of results. We believe that PLS-IRRS has the potential to become one of the primary choices to address the critical issue of unobserved heterogeneity in PLS-SEM.

AB - Uncovering unobserved heterogeneity is a requirement to obtain valid results when using the structural equation modeling (SEM) method with empirical data. Conventional segmentation methods usually fail in SEM since they account for the observations but not the latent variables and their relationships in the structural model. This research introduces a new segmentation approach to variancebased SEM. The iterative reweighted regressions segmentation method for PLS (PLS-IRRS) effectively identifies segments in data sets. In comparison with existing alternatives, PLS-IRRS is multiple times faster while delivering the same quality of results. We believe that PLS-IRRS has the potential to become one of the primary choices to address the critical issue of unobserved heterogeneity in PLS-SEM.

U2 - 10.3990/2.344

DO - 10.3990/2.344

M3 - Conference contribution

SN - 9789036540568

BT - Proceedings of the 2nd International Symposium on Partial Least Squares Path Modeling

A2 - Henseler, Jörg

A2 - Ringle, Christian

A2 - Roldán, José

A2 - Cepeda, Gabriel

PB - University of Twente

CY - Enschede

T2 - 2015 PLS User Conference

Y2 - 16 June 2015 through 19 June 2015

ER -

Segmentation of PLS path models by iterative reweighted regressions

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Research output

Proceedings of the 2nd International Symposium on Partial Least Squares Path Modeling: The Conference for PLS Users

Cite this