This study provides a methodological exploration of the ‘Lovemarks’ framework in social media marketing by replicating and extending the work of (Feta…

Combined importance–performance map analysis (cIPMA) extends partial least squares structural equation modeling (PLS-SEM) by integrating importance as…

Estimate complex Structural Equation Models (SEMs) by fitting Partial Least Squares Structural Equation Modeling (PLS-SEM) and Partial Least Squares consistent Structural Equation Modeling (PLSc-SEM) specifications that handle categorical data, non-linear relations, and multilevel structures. The implementation follows Lohmöller (1989) for the classic PLS-SEM algorithm, Dijkstra and Henseler (2015) for consistent PLSc-SEM, Dijkstra et al., (2014) for nonlinear PLSc-SEM, and Schuberth, Henseler, Dijkstra (2018) for ordinal PLS-SEM and PLSc-SEM. Additional extensions are under development. References: Lohmöller, J.-B. (1989, ISBN:9783790803002). "Latent Variable Path Modeling with Partial Least Squares." Dijkstra, T. K., &amp; Henseler, J. (2015). &lt;<a href="https://doi.org/10.1016%2Fj.jmva.2015.06.002" target="_top">doi:10.1016/j.jmva.2015.06.002</a>&gt;. "Consistent partial least squares path modeling." Dijkstra, T. K., &amp; Schermelleh-Engel, K. (2014). &lt;<a href="https://doi.org/10.1016%2Fj.csda.2014.07.008" target="_top">doi:10.1016/j.csda.2014.07.008</a>&gt;. "Consistent partial least squares for nonlinear structural equation models." Schuberth, F., Henseler, J., &amp; Dijkstra, T. K. (2018). &lt;<a href="https://doi.org/10.1007%2Fs11135-018-0767-9" target="_top">doi:10.1007/s11135-018-0767-9</a>&gt;. "Partial least squares path modeling using ordinal categorical indicators."

NCA software is a comprehensive but straightforward tool for a complete evaluation of data.