Congestion charging was as a trial introduced in Stockholm from January 3rd to July 31st 2006. After the referendum in September 2006, the charging system was finally introduced as permanent from August 2007 with some adjustments to the Trial design. The idea of congestion charging is unique in a Swedish context, and the introduction of the Stockholm system has been highly controversial. Considerable efforts have therefore been undertaken to provide information that could serve as Decision Support along the way. This has included e.g. modelling and forecasts before the Trial, a comprehensive evaluation programme during the Trial, extensive stakeholder consultations throughout, and various information and communication strategies. But what difference did this information input make, and what was its role in the process from initiating the system, to its final adoption? In this paper we pave the way for investigating the use and role of Decision Support in the Stockholm Congestion Charging experiment. We adopt a definition of Decision Support as the systematic application of externally produced knowledge in transport planning and policy making processes. We then derive an analytical framework from the research literature on knowledge utilization in policy making. This research has generally found that both technical, communicative, and institutional aspects of the Decision Support matter for its influence on actual policy making processes and results. In our analysis we find a similar pattern. This high technical quality of the monitoring and evaluation programmes provided for solid verified results, while the institutional arrangements and the communication strategies helped to ensure the credibility and legitimacy of the information for the decision makers. The availability of rich contents coupled with strategies for the timely and targeted information delivery suggest that direct instrumental use could have taken place. At a more general level the Trial represents an advanced form of Decision Support that goes beyond the mere application of calculated results to encompass a process where the decision parameters themselves become part of the change process. (A) Reprinted with permission from Elsevier.
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