ENHANCING PARTICIPATIVE POLICY MAKING THROUGH MODELLING AND SIMULATION: A STATE OF THE ART REVIEW

While previously public policy making was predominantly technocratic, based mainly on ‘first generation’ approaches employing mathematical optimization algorithms, in the last thirty years it has become much more participative, adopting ‘second generation’ approaches which involve the affected citizens to a continuously increasing extent. This trend has been reinforced by the explosive growth of the information and communication technologies (ICT) and especially the Internet, resulting to the development of e-participation. Public participation provides to the competent government organizations useful information on citizens’ interest in and acceptance of public policies under formation or application, and also numerous proposals for changes, improvements and enhancements of them. It is therefore necessary to support and enhance participative policy making with technocratic mechanisms and tools for screening these proposals and analysing them as to their outcomes, and also for forecasting the future evolution of citizens’ interest in and acceptance of them. The use of simulation can be a very useful tool for these purposes. In this paper we present a state of the art review of existing modelling and simulation approaches from the above perspective. In particular, we examine Discrete Event Modelling and Simulation, Monte Carlo Simulation, System Dynamics, Dynamic Systems, Cellular Automata and Agent-Based Modelling and Simulation. From this investigation it is concluded that System Dynamics seems to be the most promising for the above purposes, followed by Agent-Based Modelling and Simulation, and that both can contribute significantly to the technocratic enhancement of participative policy making.