Estimating and assessing second-order constructs using PLS-PM: the case of composites of composites

Abstract

PurposeThe purpose of this study is threefold: (1) to propose partial least squares path modeling (PLS-PM) as a way to estimate models containing composites of composites and to compare the performance of the PLS-PM approaches in this context, (2) to provide and evaluate two testing procedures to assess the overall fit of such models and (3) to introduce user-friendly step-by-step guidelines.Design/methodology/approachA simulation is conducted to examine the PLS-PM approaches and the performance of the two proposed testing procedures.FindingsThe simulation results show that the two-stage approach, its combination with the repeated indicators approach and the extended repeated indicators approach perform similarly. However, only the former is Fisher consistent. Moreover, the simulation shows that guidelines neglecting model fit assessment miss an important opportunity to detect misspecified models. Finally, the results show that both testing procedures based on the two-stage approach allow for assessment of the model fit.Practical implicationsAnalysts who estimate and assess models containing composites of composites should use the authors’ guidelines, since the majority of existing guidelines neglect model fit assessment and thus omit a crucial step of structural equation modeling.Originality/valueThis study contributes to the understanding of the discussed approaches. Moreover, it highlights the importance of overall model fit assessment and provides insights about testing the fit of models containing composites of composites. Based on these findings, step-by-step guidelines are introduced to estimate and assess models containing composites of composites.

Confirmatory composite analysis using partial least squares: setting the record straight

“…(1) j = I j ∑ i=1 w ji ⋅ y ji 2 Although the study at hand focus only emergent variables composed by observable variables, in general, emergent variables can be also made up by latent or other emergent variables, see for example van Riel et al (2017) and Schuberth et al (2020).…”

Guest editorial

“…Schuberth et al (2021) focus on the second-order construct in PLS-SEM modeling which is a prevailing way to operationalize complex theoretical concepts in information systems research. Schuberth et al (2021) differentiate four types of second-order constructs – common factors of common factors, common factors of composites, composites of common factors and composites of composites.…”

“…Schuberth et al (2021) focus on the second-order construct in PLS-SEM modeling which is a prevailing way to operationalize complex theoretical concepts in information systems research. Schuberth et al (2021) differentiate four types of second-order constructs – common factors of common factors, common factors of composites, composites of common factors and composites of composites. Among these four types of constructs, composites of composites, which can be used to operationalize concepts that consist of other composed concepts, has been employed the most to model second-order constructs in IS research.…”

“…However, despite its practical importance and relevance, the evaluation of composites of composites remains underexplored in the structural equational modeling (SEM) literature. Motivated by this research gap, Schuberth et al (2021) aim to: (1) show how to estimate composites of composites in PLS-SEM by comparing the performance of different PLS-SEM approaches; (2) propose and evaluate two procedures to assess the overall model fit of models containing composites of composites and (3) provide a user-friendly step-by-step guideline demonstrating how to estimate such models. To this end, Schuberth et al (2021) first review the existing approaches to estimate models containing composites: repeated indicators approach, the two-stage approach, the hybrid approach and modified versions of these approaches.…”

“…Motivated by this research gap, Schuberth et al (2021) aim to: (1) show how to estimate composites of composites in PLS-SEM by comparing the performance of different PLS-SEM approaches; (2) propose and evaluate two procedures to assess the overall model fit of models containing composites of composites and (3) provide a user-friendly step-by-step guideline demonstrating how to estimate such models. To this end, Schuberth et al (2021) first review the existing approaches to estimate models containing composites: repeated indicators approach, the two-stage approach, the hybrid approach and modified versions of these approaches. Next, Schuberth et al (2021) introduce two strategies to assess the overall fit of such models: (1) following a two-step testing procedure and (2) assessing the complete postulated model all at once.…”