Construct validity in partial least squares path modeling

Mikko Rönkkö*, Jukka Ylitalo

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    25 Citations (Scopus)


    Partial least squares path modeling (PLS) has seen increased use in the information systems research community. One of the stated key advantages of PLS is that it weights the indicator variables based on the strength of the relationship between the indicators and the underlying constructs, which presumably decreases the effect of measurement error in the analysis results. In this paper we argue that this assumption is not valid. While PLS indeed does weight the indicators to maximize the explained variance, it does this by including error variance in the model thus reducing construct validity. We use a simulation study of a simple PLS model to show that when compared to traditional sum scale approach, PLS estimates are actually often less valid. Although our study has its limitations, it hints that the use of PLS as a theory testing tool should be reevaluated and that more research testing the effectiveness of the PLS approach is in order.

    Original languageEnglish
    Title of host publicationICIS 2010 Proceedings - Thirty First International Conference on Information Systems
    Publication statusPublished - 1 Dec 2010
    MoE publication typeA4 Article in a conference publication
    EventInternational Conference on Information Systems - St. Louis, United States
    Duration: 12 Dec 201015 Dec 2010
    Conference number: 31


    ConferenceInternational Conference on Information Systems
    Abbreviated titleICIS
    Country/TerritoryUnited States
    CitySt. Louis


    • Construct validity
    • Monte carlo simulation
    • Partial least squares


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