No abstract

No abstract

Abstract. The paper presents a policy analysis framework developed through a process of interdisciplinary integration as well as through a process of end users needs elicitation. The proposed framework constitutes the theoretical foundation for the Decision Support Component of a technological platform bringing together Social Media and System Dynamics simulation developed within the PADGETS project. The main novelties introduced have to do with the possibility to provide decision makers with a set of concise, fresh and relevant data in a cost effective and easily understandable way.

Governments have started increasingly using web 2.0 social media as a new channel of interaction with citizens in various phases of public policies lifecycle. In this direction they have started moving from simpler forms of exploitation of these strong bi-directional communication channels to more complex and sophisticated ones. These attempts constitute important innovations for government agencies, so it is necessary to analyse them from this perspective as well. This paper analyzes an advanced form of centralised use of multiple social media by government agencies from this perspective, using the well established Diffusion of Innovations Theory of Rogers. It is based on a pilot application of the above approach for conducting a consultation campaign in multiple social media concerning the large scale application of a telemedicine program of the Piedmont Regional Government, Italy. It has been concluded that this approach has the fundamental preconditions for a wide diffusion (relative advantage, compatibility with existing values and processes, reasonable complexity, trialability and observability), at least in government organizations having a tradition of bi-directional communication with citizens in all phases of policy making, and also some experience in using social media for this purpose.

This paper describes a knowledge-based decision support system (KB-DSS) to improve the preparedness of crisis situations induced by natural and technological hazards. The proposed KB-DSS aims to manage the potential cascading effects generated by a triggering hazard assessing the possible event time histories based on interconnected probabilistic simulation models. From a methodological point of view, a decision model based on two Multi-Criteria Decision-Making (MCDM) algorithms follows a cascading effect simulation model. This combination allows to support the decision maker in comparing a set of mitigation strategies on the basis of their expected impacts and his priorities. The algorithm is based on an ensemble approach, which combines decisions over an array of possible impact scenarios, instead of only relying on the average impact scenario. An application of the KB-DSS to the case of a possible reactivation of Nea Kameni volcano in Santorini is presented to show how the proposed architecture could be applied to a real case. The proposed methodology supports the emergency planners in making the best decisions supporting them also in the choice of the best timing for the intervention.