Editor's comments: PLS: a silver bullet?

By George A. Marcoulides, Carol Stoak Saunders. 2006

523 citations recorded by the source corpus.

Subfields: Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/1e96b8f28ec09b9b9ca2246eae7c9c9fbed124b3

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In Sociology and Political Science

Citations in the corpus

The effects of retail channel integration through the use of information technologies on firm performance (2012, background): “…assuring the psychometric properties of the measurement model, the PLS structural model was next assessed to determine the significance of the hypothesized paths and its explanatory power based on the amount of variance accounted for by the endogenous constructs (Marcoulides and Saunders, 2006).”
Teachers’ emotional labour, discrete emotions, and classroom management self-efficacy (2018, background): “This is because the appropriate sample size depends on many elements such as the psychometric properties of the variables, the strength of the relationships among the variables, the model complexity, the amount of missing data and so on (Marcoulides & Saunders, 2006).”
Using Partial Least Squares in Operations Management Research: A Practical Guideline and Summary of Past Research (2012, background): “Thus, the literature calls for researchers to calculate statistical power to determine sample size adequacy (Marcoulides and Saunders, 2006).”
Salesperson ambidexterity and customer satisfaction: examining the role of customer demandingness, adaptive selling, and role conflict (2017, methodology): “Partial least square (PLS) analysis is particularly appropriate when studying complex models with small sample sizes (Chin, Marcolin, and Newsted 2003; Hair, Ringle, and Sarstedt 2011; Marcoulides and Saunders 2006).”
Using PLS path modeling in new technology research: updated guidelines (2016, background): “PLS is widely used in information systems research (Marcoulides and Saunders, 2006), strategic management (Hair et al., 2012a), marketing (Hair et al., 2012b), and beyond.”
Common Beliefs and Reality About PLS (2014, background): “This topic has been passionately debated in recent years (e.g., Marcoulides & Saunders, 2006) and has been empirically examined in various simulation studies (e.g., Areskoug, 1982; Goodhue et al., 2012; Hulland et al., 2010; Lu et al., 2011; Reinartz et al., 2009; Vilares & Coelho, 2013).”
Effects of entrepreneurial knowledge on entrepreneurial intentions: a longitudinal study of selected South-east Asian business students (2014, methodology): “The current study has met the guidelines set by Marcoulides and Saunders (2006) in terms of PLS estimation, after taking into account the main objective of the study (i.e. estimating relationships rather than predictive modelling), the sample size of 245 individuals, 19 indicators, 4 latent…”
Longitudinal Pathways From Math Intrinsic Motivation and Achievement to Math Course Accomplishments and Educational Attainment (2013, methodology): “…the sample size requirement to reject the hypothesis that a particular path coefficient is 0 increases to 109 for a power of 0.85 (see B. O. Muthén & Muthén, 2002, and Marcoulides & Saunders, 2006, and appendices therein for setups on how to conduct such Monte Carlo analyses using Mplus).”
Editor's comments: a critical look at the use of PLS-SEM in MIS quarterly (2012, methodology): “This issue has been passionately debated over the last years (e.g., Goodhue et al. 2006; Marcoulides and Saunders 2006) with Gefen et al. (2011, p. iii) noting that there is an “apparent misuse of perceived leniencies such as assumptions about minimum sample sizes.””