Applying Maximum Likelihood and PLS on Different Sample Sizes: Studies on SERVQUAL Model and Employee Behavior Model

By C. Barroso, Gabriel Cepeda Carrion, José L. Roldán. 2010

374 citations recorded by the source corpus.

Subfields: Information Systems and Management, Marketing, Organizational Behavior and Human Resource Management

View Paper: https://www.semanticscholar.org/paper/5f116d12c3e6a8d83052892818cc15dbe2af7041

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Citations in the corpus

Absorptive capacity and relationship learning mechanisms as complementary drivers of green innovation performance (2018, methodology): “This technique enables the assessment of the reliability and validity of the measures of theoretical constructs –outer model– and the estimation of the relationships among these constructs –inner model (Barroso et al., 2010; Hair et al., 2011).”
The impacts of brand experiences on brand loyalty: mediators of brand love and trust (2017, neutral): “(Barroso et al., 2010; Hair et al., 2011; 2014).”
Adoption of artificial intelligence in higher education: a quantitative analysis using structural equation modelling (2020, background): “The lowest permissible value of LF is 0.707 (Borroso et al. 2010), of Composite Reliability (CR) of each construct is 0.5 (Hair et al. 2011) and of AVE is 0.7 (Urbach and Ahlemann 2011).”
Using Partial Least Squares in Operations Management Research: A Practical Guideline and Summary of Past Research (2012, result): “In fact, “CBSEM and PLS are considered as complementary rather than competitive methods, and both have a rigorous rationale of their own” (Barroso et al., 2010, p. 432). estima ted as the correlatio n betw een the late nt variab le (LV) item scores of each refl ective item are regressed on LV…”
Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods (2017, methodology): “…prior research regarding the performance of PLS and GSCA using factor model-based populations, where these methods have been shown to overestimate measurement model parameters and underestimate structural model parameters (e.g., Barroso et al. 2010; Chin et al. 2003; Reinartz et al. 2009).”