Combined Importance Performance Map Analysis (cIPMA)

We thank Jeisson Alexander Higuera Reina for producing this video that
accompanies our research on combining the importance-performance map analysis (IPMA) in partial least squares structural equation modeling (PLS-SEM) with findings from necessary condition analysis (NCA).

The IPMA comprises assessing latent variables and their indicators' importance and performance, while an NCA introduces an additional dimension by identifying factors that are crucial for achieving the desired outcomes. An NCA employs necessity logic to identify the must-have factors required for an outcome, while PLS-SEM employs additive sufficiency logic to identify the should-have factors that contribute to high performance levels. Integrating these two logics into the performance dimension is particularly valuable for prioritizing actions that could improve the target outcomes. We propose and illustrate how to combine NCA with IPMA in a combined IPMA (cIPMA).

Please find the references to the relevant manuscripts below, as well as links to download the illustrative dataset and toolset:

Baseline article:
Hauff/Richter/Sarstedt/Ringle (2024). Importance and performance in PLS-SEM and NCA: Introducing the combined importance-performance map analysis (cIPMA). Journal of Retailing and Consumer Services, 78 (2024).

Illustration and tutorial in SmartPLS:

Dataset description and download link:
Open access:

Excel-toolset download link:

Recommended illustration at the end of the video:
Riggs/Felipe/Roldán/Real (2024). Deepening big data sustainable value creation: Insights using IPMA, NCA, and cIPMA. Journal of Marketing Analytics (2024).

Video production by:
D. Jeisson A. Higuera Reina
(Universidad De Sevilla)
Nicole Richter
(University of Southern Denmark)

We hope that this material will be helpful for your research projects!