Structural model robustness checks in PLS-SEM

Partial least squares structural equation modeling (PLS-SEM) has become a standard tool for analyzing complex inter-relationships between observed and latent variables in tourism and numerous other fields of scientific inquiry. Along with the recent surge in the method’s use, research has contribute...

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Main Authors: Sarstedt, Marko, Ringle, Christian M., Cheah, Jun-Hwa, Ting, Hiram, Moisescu, Ovidiu I., Radomir, Lacramioara
Format: Article
Published: Sage Publications 2020
Online Access:http://psasir.upm.edu.my/id/eprint/85944/
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author Sarstedt, Marko
Ringle, Christian M.
Cheah, Jun-Hwa
Ting, Hiram
Moisescu, Ovidiu I.
Radomir, Lacramioara
author_facet Sarstedt, Marko
Ringle, Christian M.
Cheah, Jun-Hwa
Ting, Hiram
Moisescu, Ovidiu I.
Radomir, Lacramioara
author_sort Sarstedt, Marko
building UPM Institutional Repository
collection Online Access
description Partial least squares structural equation modeling (PLS-SEM) has become a standard tool for analyzing complex inter-relationships between observed and latent variables in tourism and numerous other fields of scientific inquiry. Along with the recent surge in the method’s use, research has contributed several complementary methods for assessing the robustness of PLS-SEM results. Although these improvements are documented in extant literature, research on tourism has been slow to adopt the relevant complementary methods. This article illustrates the use of recent advances in PLS-SEM, designed to ensure structural model results’ robustness in terms of nonlinear effects, endogeneity, and unobserved heterogeneity in a PLS-SEM framework. Our overarching aim is to encourage the routine use of these complementary methods to increase methodological rigor in the field.
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institution Universiti Putra Malaysia
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spelling upm-859442023-11-28T03:09:49Z http://psasir.upm.edu.my/id/eprint/85944/ Structural model robustness checks in PLS-SEM Sarstedt, Marko Ringle, Christian M. Cheah, Jun-Hwa Ting, Hiram Moisescu, Ovidiu I. Radomir, Lacramioara Partial least squares structural equation modeling (PLS-SEM) has become a standard tool for analyzing complex inter-relationships between observed and latent variables in tourism and numerous other fields of scientific inquiry. Along with the recent surge in the method’s use, research has contributed several complementary methods for assessing the robustness of PLS-SEM results. Although these improvements are documented in extant literature, research on tourism has been slow to adopt the relevant complementary methods. This article illustrates the use of recent advances in PLS-SEM, designed to ensure structural model results’ robustness in terms of nonlinear effects, endogeneity, and unobserved heterogeneity in a PLS-SEM framework. Our overarching aim is to encourage the routine use of these complementary methods to increase methodological rigor in the field. Sage Publications 2020 Article PeerReviewed Sarstedt, Marko and Ringle, Christian M. and Cheah, Jun-Hwa and Ting, Hiram and Moisescu, Ovidiu I. and Radomir, Lacramioara (2020) Structural model robustness checks in PLS-SEM. Tourism Economics, 26 (4). 531 - 554. ISSN 1354-8166; ESSN: 2044-0375 https://journals.sagepub.com/doi/10.1177/1354816618823921 10.1177/1354816618823921
spellingShingle Sarstedt, Marko
Ringle, Christian M.
Cheah, Jun-Hwa
Ting, Hiram
Moisescu, Ovidiu I.
Radomir, Lacramioara
Structural model robustness checks in PLS-SEM
title Structural model robustness checks in PLS-SEM
title_full Structural model robustness checks in PLS-SEM
title_fullStr Structural model robustness checks in PLS-SEM
title_full_unstemmed Structural model robustness checks in PLS-SEM
title_short Structural model robustness checks in PLS-SEM
title_sort structural model robustness checks in pls-sem
url http://psasir.upm.edu.my/id/eprint/85944/
http://psasir.upm.edu.my/id/eprint/85944/
http://psasir.upm.edu.my/id/eprint/85944/