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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my.upm.eprints.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 |
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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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Article |
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Sarstedt, Marko Ringle, Christian M. Cheah, Jun-Hwa Ting, Hiram Moisescu, Ovidiu I. Radomir, Lacramioara |
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Sarstedt, Marko Ringle, Christian M. Cheah, Jun-Hwa Ting, Hiram Moisescu, Ovidiu I. Radomir, Lacramioara Structural model robustness checks in PLS-SEM |
author_facet |
Sarstedt, Marko Ringle, Christian M. Cheah, Jun-Hwa Ting, Hiram Moisescu, Ovidiu I. Radomir, Lacramioara |
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Sarstedt, Marko |
title |
Structural model robustness checks in PLS-SEM |
title_short |
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_sort |
structural model robustness checks in pls-sem |
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Sage Publications |
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2020 |
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http://psasir.upm.edu.my/id/eprint/85944/ https://journals.sagepub.com/doi/10.1177/1354816618823921 |
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