The PLS Agent: Predictive Modeling with PLS-SEM and Agent-Based Simulation

Posted: 13 Jun 2017

See all articles by Sandra Schubring

Sandra Schubring

Hamburg University of Technology

Iris Lorscheid

Hamburg University of Technology

Matthias Meyer

Hamburg University of Technology

Christian M. Ringle

Hamburg University of Technology (TUHH); Waikato Management School

Date Written: September 1, 2015

Abstract

Partial least squares structural equation modeling (PLS-SEM) is a widespread multivariate analysis method that is used to estimate variance-based structural equation models.However, the PLS-SEM results are to some extent static in that they usually build on cross-sectional data. The combination of two modeling methods―agent-based simulation (ABS) and PLS-SEM―makes PLS-SEM results dynamic and extends their predictive range. The dynamic ABS modeling method uses a static path model and PLS-SEM results to determine the ABS settings at the agent level. Besides presenting the conceptual underpinnings of the PLS agent, this research includes an empirical application of the well-known technology acceptance model. In this illustration, the ABS extends the PLS path model's predictive capability from the individual level to the population level by modeling the diffusion process in a consumer network. This study contributes to the recent research stream on predictive modeling by introducing the PLS agent and presenting dynamic PLS-SEM results.

Keywords: Partial least squares path modeling, PLS-SEM, Agent-based simulation, ABS, Predictive modeling, TAM

Suggested Citation

Schubring, Sandra and Lorscheid, Iris and Meyer, Matthias and Ringle, Christian M., The PLS Agent: Predictive Modeling with PLS-SEM and Agent-Based Simulation (September 1, 2015). Journal of Business Research, Vol. 69, No. 10, 2016. Available at SSRN: https://ssrn.com/abstract=2984784

Sandra Schubring (Contact Author)

Hamburg University of Technology ( email )

Schwarzenbergstrasse 95
Hamburg, DE Hamburg 21073
Germany

Iris Lorscheid

Hamburg University of Technology ( email )

Schwarzenbergstrasse 95
Hamburg, DE Hamburg 21073
Germany

Matthias Meyer

Hamburg University of Technology ( email )

Schwarzenbergstrasse 95
Hamburg, DE Hamburg 21073
Germany

Christian M. Ringle

Hamburg University of Technology (TUHH) ( email )

Schwarzenbergstr. 95 (D)
Hamburg, D-21071
Germany

HOME PAGE: http://www.tuhh.de/hrmo

Waikato Management School ( email )

Te Raupapa
Private Bag 3105
Hamilton, 3240
New Zealand

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