Partial least squares structural equation modeling using SmartPLS: a software review
By Marko Sarstedt, Jun-Hwa (Jacky) Cheah. Journal of Marketing Analytics, 2019
779 citations recorded by the source corpus.
Subfields: Marketing, Organizational Behavior and Human Resource Management, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/fe4dc7b46261e1bcffc0942b77f0717ceaa11d6d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Marketing
- Hiram Ting
- José L. Roldán
- Thurasamy Ramayah
- Enrico Ciavolino
- Mumtaz Ali Memon
- Francis Chuah
- Ramayah Thurasamy
- Jun-Hwa (Jacky) Cheah
In Organizational Behavior and Human Resource Management
- Hiram Ting
- Jun-Hwa (Jacky) Cheah
- José L. Roldán
- Thurasamy Ramayah
- Enrico Ciavolino
- Mumtaz Ali Memon
- Francis Chuah
- Ramayah Thurasamy
In Sociology and Political Science
- Thurasamy Ramayah
- Hiram Ting
- Mumtaz Ali Memon
- Francis Chuah
- José L. Roldán
- Enrico Ciavolino
- Ramayah Thurasamy
- Jun-Hwa (Jacky) Cheah
Citations in the corpus
- Multigroup Analysis using SmartPLS: Step-by-Step Guidelines for Business Research (2020, positive): “SmartPLS 3.3.2 was used to illustrate the MGA assessment (Ringle et al., 2015; Sarstedt and Cheah, 2019).”
- Sampling weight adjustments in partial least squares structural equation modeling: guidelines and illustrations (2020, methodology): “Even though the WPLS algorithm has been incorporated in SmartPLS software at both the setting of the PLS algorithm and bootstrapping (Sarstedt & Cheah, 2019), future studies should extend this procedure as part of the weighted parameter estimation in PLSpredict (Shmueli et al., 2019).”