Agent-Based Modelling of Organizational Performance

Abstract

In a Complex Adaptive System (CAS) such as healthcare, co-evolution of the agents and the system produces emergent order. Investigations into drivers of organizational performance reveal the importance of coherent group effort (Organizational Culture) as well as strategy. Non-linear improvements in performance result as Organizational Culture advances. These advances are heavily dependent upon starting point and exhibit path dependency. We developed a NetLogo^TMagent-based model showing the evolution of Organizational Culture based upon selected starting points of Organizational Culture, Values, Purpose, Intellectual Capital and Perspective. Parameters change in accordance with interactions of the agents in time and space as well as the impact of both planned and stochastic external variables on the parameters. We used the biologic allometric scaling equation, y = kx ^α, reasoning that Organizational Productivity behaves in the organization like biologic variables behave in the organism. At baseline, the model consistently mirrors a 10-year empiric study of real-world organizations. Without intervention, Organizational Culture reaches an asymptotic maximum with minimal, linear improvement in performance over time. By altering the starting point, or by closing “structural holes” in the organization, Organizational Culture passes through phase-transitions with resulting non-linear increase in Organizational Performance.