Estimating hierarchical constructs using consistent partial least squares: The case of second-order composites of common factors

Allard C.R. van Riel, Jörg Henseler, Ildiko Kemeny, Zuzana Sasovova

Research output: Contribution to journalArticleAcademicpeer-review

47 Citations (Scopus)
165 Downloads (Pure)

Abstract

Purpose
Many important constructs of business and social sciences are conceptualized as composites of common factors, i.e. as second-order constructs composed of reflectively measured first-order constructs. Current approaches to model this type of second-order construct provide inconsistent estimates and lack a model test that helps assess the existence and/or usefulness of a second-order construct. The purpose of this paper is to present a novel three-stage approach to model, estimate, and test second-order constructs composed of reflectively measured first-order constructs.

Design/methodology/approach
The authors compare the efficacy of the proposed three-stage approach with that of the dominant extant approaches, i.e. the repeated indicator approach, the two-stage approach, and the hybrid approach by means of simulated data whose underlying population model is known. Moreover, the authors apply the three-stage approach to a real research setting in business research.

Findings
The study based on simulated data illustrates that the three-stage approach is Fisher-consistent, whereas the dominant extant approaches are not. The study based on real data shows that the three-stage approach is meaningfully applicable in typical research settings of business research. Its results can differ substantially from those of the extant approaches.

Research limitations/implications
Analysts aiming at modeling composites of common factors should apply the proposed procedure in order to test the existence and/or usefulness of a second-order construct and to obtain consistent estimates.

Originality/value
The three-stage approach is the only consistent approach for modeling, estimating, and testing composite second-order constructs made up of reflectively measured first-order constructs.
Original languageEnglish
Pages (from-to)459-477
JournalIndustrial management & data systems
Volume117
Issue number3
DOIs
Publication statusPublished - 2017

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