A Comprehensive Guide to Necessary Condition Analysis using PLS SEM SmartPLS4

Discover Necessary Condition Analysis (NCA) with PLS-SEM in SmartPLS4 and unlock deeper insights into your data. Learn how to identify variables essential for achieving desired outcomes, even if they're not sufficient on their own.

This video covers:
What is NCA, and how does it differ from SEM?
When to use NCA in your research
A step-by-step guide to conducting NCA in SmartPLS4
Interpreting NCA results for actionable insights
Tips and best practices for successful NCA
NCA when Condition is not Necessary
NCA with Formative Constructs

Correction: Apologies for the mistake. In one of the slides, loyalty is mentioned as the DV. The DV is OP not Loyalty.

Reference Articles:
Richter, N. F., Hauff, S., Ringle, C. M., Sarstedt, M., Kolev, A. E., & Schubring, S. (2023). How to apply necessary condition analysis in PLS-SEM. In Partial least squares path modeling: Basic concepts, methodological issues and applications (pp. 267-297). Cham: Springer International Publishing.

Richter, N. F., Schubring, S., Hauff, S., Ringle, C. M., & Sarstedt, M. (2020). When predictors of outcomes are necessary: Guidelines for the combined use of PLS-SEM and NCA. Industrial management & data systems, 120(12), 2243-2267.

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