On the role of partial least squares in path analysis for the social sciences

R. Dennis Cook and Liliana Forzani

Journal of Business Research, 2023, vol. 167, issue C

Abstract: We describe the current and potential future roles for partial least squares (PLS) algorithms in path analyses, guided by recent advances in envelope theory. After reviewing the present debate and establishing a context, we conclude that, depending on specific objectives, PLS methods have considerable promise, but that their full potential, while reachable, is not now being realized. The future developments necessary for achieving their full potential in the social sciences are clear and doable, albeit demanding. A critique of covariance-based structural equation modeling (CB-SEM), as it relates to PLS, is given as well. Technical details are available in the appendix.

Keywords: Envelopes; Reduced rank regression; Reflective path models; Structural equation modeling (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0148296323004915
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:167:y:2023:i:c:s0148296323004915

DOI: 10.1016/j.jbusres.2023.114132

Access Statistics for this article

Journal of Business Research is currently edited by A. G. Woodside

More articles in Journal of Business Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().