A primer on partial least squares structural equation modeling (PLS-SEM)
By Joseph F. Hair, G. Tomas M. Hult, Christian M. Ringle, Marko Sarstedt. 2013
1,279 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/3e803ab1aaa0c28fb6106f1a3b5ab42fe2655a40
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Citations in the corpus
- Digital content marketing as a catalyst for e-WOM in food tourism (2020, unknown): “Table 3 illustrates that there was no redundancy or multi-collinearity violations with the correlations, which all were less than the 0.90 cut-off range of between 0.613 and 0.871 (Hair et al., 2014).”
- On the Emancipation of PLS-SEM: A Commentary on Rigdon (2012) (2014, unknown): “In analogy to the f 2 effect size, researchers can compute the q2 effect size, which allows for evaluating the relative impact of one construct in terms of its predictive relevance (Chin 1998; Hair et al., 2014).”
- Marketing innovation and sustainable competitive advantage of manufacturing SMEs in Ghana (2019, unknown): “The reliability test involved two main criteria comprising CA (Cronbach, 1951) and the CR (Hair et al., 2014, 2015).”
- Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making (2021, methodology): “The minimum sample size requirement can be determined based on the expected minimum R2 values of constructs (Hair et al., 2014).”