Using the Hybrid Two-Step estimation approach for the identification of second-order latent variable models

Abstract

The aim of this paper is to define a new approach, called Hybrid Two-Step, to estimate the parameters of a second-order latent variable (LV) model in the case of formative relationships between the first-order and the second-order LVs. In this respect, we introduce the two main approaches to the estimation of second-order constructs through the partial least squares-path modelling: the so-called Repeated Indicators approach and the Two-Step approach. Some criticisms of these methodologies are highlighted and a solution to the issue of the identification of formative second-order constructs is suggested through the adoption of a Hybrid Two-Step approach. A Monte Carlo simulation study aimed at comparing the approach proposed with the traditional ones was performed. Finally, a case study about the passenger satisfaction is presented to show the implementation of the method and to give some comparative empirical results.

Keywords:

• second-order latent variables
• partial least squares
• path modelling
• passenger satisfaction
• simulation study

Acknowledgements

The authors are grateful to the reviewers for careful reading, valuable comments, and highly constructive suggestions that have led to clarity, better presentation, and improvements in the paper.