2019
DOI: 10.1108/intr-12-2017-0509
|View full text |Cite
|
Sign up to set email alerts
|

Methodological research on partial least squares structural equation modeling (PLS-SEM)

Abstract: Purpose The purpose of this paper is to explore the knowledge infrastructure of methodological research on partial least squares structural equation modeling (PLS-SEM) from a network point of view. The analysis involves the structures of authors, institutions, countries and co-citation networks, and discloses trending developments in the field. Design/methodology/approach Based on bibliometric data downloaded from the Web of Science, the authors apply various social network analysis (SNA) and visualization t… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

3
159
0
6

Year Published

2019
2019
2023
2023

Publication Types

Select...
8
1
1

Relationship

1
9

Authors

Journals

citations
Cited by 272 publications
(176 citation statements)
references
References 108 publications
3
159
0
6
Order By: Relevance
“…The primary advantages of PLS-SEM include the relaxation of normal distributional assumptions required by PLS-SEM's ability to easily estimate much more complex models with smaller sample sizes (Shiau and Chau, 2016;Hair et al, 2019;Khan et al, 2019;Shiau et al, 2019). PLS-SEM is more suitable for this study under the following situations: when the research objective is exploratory research for theory development, when the analysis is for a prediction perspective; when the structural model is complex, when the structural model includes one or more formative constructs; when distribution is lack of normality, and when research requires latent variable scores for consequent analyses (Shiau and Chau, 2016;Hair et al, 2019;Khan et al, 2019;Shiau et al, 2019). The above reasons provide supports to consider the PLS as an appropriate SEM method for a study.…”
Section: Structural Model Resultsmentioning
confidence: 99%
“…The primary advantages of PLS-SEM include the relaxation of normal distributional assumptions required by PLS-SEM's ability to easily estimate much more complex models with smaller sample sizes (Shiau and Chau, 2016;Hair et al, 2019;Khan et al, 2019;Shiau et al, 2019). PLS-SEM is more suitable for this study under the following situations: when the research objective is exploratory research for theory development, when the analysis is for a prediction perspective; when the structural model is complex, when the structural model includes one or more formative constructs; when distribution is lack of normality, and when research requires latent variable scores for consequent analyses (Shiau and Chau, 2016;Hair et al, 2019;Khan et al, 2019;Shiau et al, 2019). The above reasons provide supports to consider the PLS as an appropriate SEM method for a study.…”
Section: Structural Model Resultsmentioning
confidence: 99%
“…Furthermore, the fit of models estimated by PLS can be assessed in two ways: first, by measures of fit, such as the standardized root-mean-square residual (SRMR, Henseler et al 2014), and second by bootstrap-based tests of the overall model fit (Dijkstra and Henseler 2015a). A recent overview of the methodological research on PLS is provided by Khan et al (2019).…”
Section: Introductionmentioning
confidence: 99%
“…Across a period of years, research topics may weave in and out of popularity. One technique for measuring the appeal of a topic in research literature over time is Kleinberg's (2003) burst detection algorithm, which is well recognised on different fields using bibliometric methods (e.g., Khan et al, 2019;Zhu et al, 2019;Chen et al, 2018;Song et al, 2016;Guo et al, 2011). We applied this algorithm to identify emerging topics and radical changes or sharp increases in interest in a specific topic -called the burst -over time (e.g., Zhu et al, 2019).…”
Section: Burst Analysismentioning
confidence: 99%