The elicitation and processing of relevant information is the core of any policy decision-making process. Modelling is about making sense of the available information. Models are able to incorporate the contextual influences on policy making (e.g. political and economic environments, community sentiment…etc). Systems analysis allows quantitative, empirical testing of models that exist in the study of public policy. Simulation and visualisation techniques can help policy makers to reduce uncertainties on the possible impacts of policies. In an effort to enable adoption of the systems thinking approach to address the central problem of empirical political study, this thesis presents a framework for prescriptive policy analysis that provides decision support to: the problem definition, ex-ante impact assessment and evaluation activities carried out at the policy formulation stage of the policymaking process. We contribute a new tool for systemic modelling and simulation of public policy decision situations. It aims to facilitate the cognitive activity of representing complex mental models using system dynamics simulation modelling. Using the ’labelled causal mapping’ method, a policy-oriented problem structuring method introduced in this research, the tool bridges the gap between the user’s mental model and the explicit graphical representation in order to enable knowledge representation and system analysis. The method provides a basis for further computational decision analysis using a common policy appraisal format, a multi-criteria model with main evaluation criteria (effectiveness, efficiency, relevance, coherence and added value), linked to a set of measurable, context dependent attributes (targeted impact variables from the policy model). A web-based tool prototype has been implemented in a Node.js environment and is accessible both from a web-based graphical user interface as well as a hosted API. Multiple demonstration and test cases, from various policy areas and different EU policymaking levels, were used in several iterations of the build-evaluate cycle. This approach lead to the different studies that make up this research. / Sense4us - Data insights for policymakers and Citizens
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:su-134949 |
| Date | January 2016 |
| Creators | Ibrahim, Osama |
| Publisher | Stockholms universitet, Institutionen för data- och systemvetenskap, Stockholm |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Licentiate thesis, comprehensive summary, info:eu-repo/semantics/masterThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | Report Series / Department of Computer & Systems Sciences, 1101-8526 ; 16-011, info:eu-repo/grantAgreement/EC/FP7/611242 |
Page generated in 0.0019 seconds