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Implementing decision-making support systems (DMSS) is considered an organizationally complex and risky task that is influenced by dynamic technical and social-political issues. Consequently, DMSS implementation failures, with associated economic loses, are still reported. While several statistics-based (static) quantitative models of successful factors and qualitative (descriptive) models to implement DMSS are available, few quantitative dynamic models have been posed. In this paper, we illustrate how a dynamic simulation model of the DMSS implementation process can be designed. We use a system dynamics approach via an extended methodology, which is called critical realism-based methodology for studying soft systems dynamics. Validation is realized through 1) the theoretical validity of the model, 2) the model's capability in reproducing historical DMSS implementation paths, and 3) the model's capability in predicting new DMSS implementation paths from new cases. Simulation results suggest the adequacy of using these modeling methods to complement the knowledge on the DMSS implementation processes.