Structural model robustness checks in PLS-SEM
Monash University Malaysia · Otto-von-Guericke-Universität Magdeburg · +6 more institutions
Abstract
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…
Citation impact
- FWCI
- 139.11
- Percentile
- 100%
- References
- 118
Authors
6- MSMarko Sarstedt
Monash University Malaysia, Otto-von-Guericke-Universität Magdeburg
- CMChristian M. RingleCorresponding
Universität Hamburg, University of Waikato, Hamburg University of Technology
- JCJun‐Hwa Cheah
Universiti Putra Malaysia
- HTHiram Ting
UCSI University
- OIOvidiu Ioan Moisescu
Babeș-Bolyai University
Topics & keywords
- Robustness (evolution)
- Structural equation modeling
- Partial least squares regression
- Econometrics
- Endogeneity
- Extant taxon
- Tourism
- Latent variable
- Decent work and economic growth