Bridging Design and Behavioral Research With Variance-Based Structural Equation Modeling

By Jörg Henseler. 2017

945 citations recorded by the source corpus.

Subfields: Marketing, Organizational Behavior and Human Resource Management

View Paper: https://www.semanticscholar.org/paper/6288d076e6322951fac0f65f6d4bfb2acfcc9b16

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Citations in the corpus

Absorptive capacity and relationship learning mechanisms as complementary drivers of green innovation performance (2018, background): “If any of these tests exceeds bootstrap-based 95% (HI95) and 99% (HI99) percentiles, it is doubtful that the research model is accurate (Henseler, 2017).”
How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research (2020, methodology): “Joint assessment should begin with the evaluation of the overall fit of a model with a saturated structural model [16,118], that is, with confirmatory factor/composite analysis.”
Investigating the effects of tourist engagement on satisfaction and loyalty (2019, methodology): “Only recently, the composite model was introduced as a third way of construct modeling (Henseler, 2017).”
How do digital capabilities affect firm performance? The mediating role of technological capabilities in the “new normal” (2022, background): “…that the deviations were not signi ﬁ cant because the 99 percent bootstrap quantiles of the three measures (SRMR, the unweighted least squares discrepancy dULS, and the geodetic discrepancy dG) were more signi ﬁ cant than the original values (Henseler, 2017; Henseler, Ringle and Sarstedt, 2016).”
Confirmatory composite analysis using partial least squares: setting the record straight (2020, methodology): “2004; Henseler 2015, 2017; Schuberth et al.”
Partial least squares path modeling: Quo vadis? (2018, methodology): “In its most modern appearance, it can be regarded as a structural equation modeling (SEM) technique that can handle various forms of construct operationalizations, including reflective measurement and composite models (for a distinction, see Rigdon 2012; Henseler 2017).”
ASSESSING REFLECTIVE MODELS IN MARKETING RESEARCH: A COMPARISON BETWEEN PLS AND PLSc ESTIMATES (2018, methodology): “…PLS Basically, in the traditional PLS algorithm, once the weights are derived from the independence of the epistemic relationships between constructs and their observed indicators, the method always produces a single specific (i.e., determinate) score for each case per composite (Henseler, 2017a).”
Impact of Organizational Culture Values on Organizational Agility (2017, background): “Since this multidimensional construct is an artifact (design construct), it is expected that the indicators (or dimensions) of the composites will be correlated [59].”
Comparison Between CB-SEM and PLS-SEM: Testing and Confirming the Maqasid Syariah Quality of Life Measurement Model (2019, methodology): “…testing when the research is exploratory in nature, the data distribution is nonnormal, sample size is small, and when the model is very complex which include both reflective and formative constructs and also when the model comprises higher-order constructs (Hair et al., 2017a; Henseler, 2017).”