Importance-performance map analysis (IPMA)
Posted: Sat Oct 24, 2020 2:03 pm
Video link: https://youtu.be/QsD19-Z7T2s
Description: The importance-performance map analysis (IPMA; Ringle and Sarstedt, 2016) — also called importance-performance matrix, impact-performance map, or priority map analysis — is a useful analysis approach in PLS-SEM that extends the results of the estimated path coefficient (importance) by adding a dimension that considers the average values of the latent variable scores (performance). More precisely, the IPMA contrasts the unstandardized total effects (importance) in the structural and the average values of the latent variable scores on a scale from 0 to 100 (performance) in a graphical representation. The resulting importance-performance map permits the identification of determinants with relatively high importance and relatively low performance. These become major and high priority improvement areas with the goal to in turn increase the performance of the selected key target construct in the PLS path model. The IPMA facilitates more elaborated interpretations of PLS-SEM results.
Literature:
Ringle, C. M. and Sarstedt, M. (2016). Gain More Insight from Your PLS-SEM Results: The Importance-Performance Map Analysis. Industrial Management & Data Systems, 116(9), 1865-1986.
Description: The importance-performance map analysis (IPMA; Ringle and Sarstedt, 2016) — also called importance-performance matrix, impact-performance map, or priority map analysis — is a useful analysis approach in PLS-SEM that extends the results of the estimated path coefficient (importance) by adding a dimension that considers the average values of the latent variable scores (performance). More precisely, the IPMA contrasts the unstandardized total effects (importance) in the structural and the average values of the latent variable scores on a scale from 0 to 100 (performance) in a graphical representation. The resulting importance-performance map permits the identification of determinants with relatively high importance and relatively low performance. These become major and high priority improvement areas with the goal to in turn increase the performance of the selected key target construct in the PLS path model. The IPMA facilitates more elaborated interpretations of PLS-SEM results.
Literature:
Ringle, C. M. and Sarstedt, M. (2016). Gain More Insight from Your PLS-SEM Results: The Importance-Performance Map Analysis. Industrial Management & Data Systems, 116(9), 1865-1986.