Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods

By Ned Kock, Pierre Hadaya. Information Systems Journal, 2018

2,261 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e60b49d8b2f63c0bf25c15be27d8bc6879378a6d

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In Artificial Intelligence

Citations in the corpus

On Comparing Results from CB-SEM and PLS-SEM: Five Perspectives and Five Recommendations (2017, background): “Numerous studies have called the legitimacy of the ten times rule into question (e.g., Goodhue et al., 2012; Kock & Hadaya, 2017; Rönkkö & Evermann, 2013), including two that used composite model data in their analyses.”
Effects of perceived service quality, website quality, and reputation on purchase intention: The mediating and moderating roles of trust and perceived risk in online shopping (2021, methodology): “We employed Harman’s single factor and full collinearity tests to ensure CMB-free data.”
Unearthing the determinants of Blockchain adoption in supply chain management (2020, methodology): “The study employed the gamma-exponential method from (Kock and Hadaya 2018).”
Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation (2021, neutral): “Two alternative approaches, the inverse square root and the gamma-exponential criteria (Kock & Hadaya, 2018), were also applied: assuming a minimum magnitude for path coefficients equal to 0.2 (corresponding to a small effect size; Cohen, 1988), we found that a minimum sample size of 215 and 199,…”
Methods and Rule-of-Thumbs in The Determination of Minimum Sample Size When Appling Structural Equation Modelling: A Review (2020, methodology): “…that though the Monte Carlo simulation method is a prominent method for determining the minimum sample size it is a difficult way and for which both technical and methodological expertise with good computer programming skills is required as well as it is time-consuming (Kock & Hadaya, 2018).”
Changes in Consumers’ Purchase Patterns as a Consequence of the COVID-19 Pandemic (2021, methodology): “95, and the inverse square root method [44], a minimum sample of 384 respondents was calculated.”