Increasing freight transportation volumes continue to increase problems related to human health, congestion on the transport infrastructure, noise, climate changes, etc. Governments often want to minimize these negative effects, and this wish is expressed in societal goals, e.g., to reach environmental targets. An important instrument for reaching societal goals is governmental control policies, e.g., regulations, taxes and fees, which can influence the behaviour of the actors in a transport chain. Before implementing such control policies, it is crucial to predict their effects in order to make probable that it is a good measure. A review of models that consider the effects of governmental control policies on transportation has been performed which shows that macro-level models are mainly used for this purpose. However, the behaviour of the individual transport chain actors can hardly be captured in such models since the decision making actors are not modelled explicitly. Consequently, the negative effects caused by the decisions taken by the individual transport chain actors are not fully captured in these models. We believe that micro-level models have the potential to bridge the gap between governmental policy-making and the behaviour of transport chain actors. A micro-level model based on agent-technology has been developed which captures the environmental, quality and economical performance in transport chains, given different governmental control policies. The transport chain actors are represented by decision-making agents in the model. Logistical factors for characterizing transport chains have been identified and described according to degree of influence. To illustrate the usage of the micro-level model, simulation experiments based on a real world case have been performed where different levels of governmental control policies are introduced. The simulation results so far have showed that the model seems to simulate the behaviour of the transport chain actors correctly in the studied scenarios. The simulation tool can then be used as a decision support for policy-makers and serve as a complement to existing tools based on macro-level models.