|Title: The PLS Agent: Predictive Modeling with Partial Least Squares and Agent-Based Simulation|
|Written by: Schubring, Sandra and Lorscheid, Iris and Meyer, Matthias and Ringle, Christian M.|
|in: June 2015 2015|
|Publisher: 2nd International Symposium on Partial Least Squares Path Modeling|
|Type: Conference Paper|
Abstract: Partial least squares structural equation modeling (PLS-SEM) is a widespread multivariate analysis method that is used to measure variance-based structural equation models. However, the results generated from PLS-SEM are static and cannot provide any information as to what might happen if one influential factor changed over time. The combination of two modeling methods, agent-based simulation (ABS) and PLS-SEM, allows us to make PLS-SEM results dynamic. We contribute to existing research by introducing the PLS Agent, which uses the static path model and PLS-SEM results to determine the settings of the dynamic ABS model-ing method. Besides presenting the conceptual underpinnings of the PLS Agent, this research includes an empirical application of the new approach to the well-known technology acceptance model.