Based on the theoretical framework and the related research questions the methodology of SI-DRIVE will focus on mapping, analyzing and promoting social innovations in Europe and other world regions to better understand and enable social innovations and their capacity for changing societies. This will include the identification and assessment of success factors, barriers and drivers of Social Innovation in the seven policy areas, supporting reciprocal empowerment in various countries and social groups to engage in Social Innovation for development, working towards Europe 2020 targets and sustainable development (e.g. Millennium Development Goals).

New evidence will be reached through a mapping approach and cyclical iteration between theory development, empirical improvements, and policy recommendations. Based on a global mapping of Social Innovation and selected in-depth case studies the research approach and results will be continuously updated. Within a mix of qualitative and quantitative methods and instrument the theoretical approach and research propositions will be proofed and further developed. Policy recommendations and foresight will be supported as well continuously in iterations throughout the duration of the project. This will allow the research team to inject new empirical based knowledge into the project and conduct future research into social innovation as new innovations evolve within the individual policy domains. The SI-DRIVE methodology will ensure theoretical based, future-oriented policy-driven research and the development of tools and instruments for policy interventions.

After two mapping exercises at European and global level (see “MAPPING”) case studies will be further analysed, used in stakeholder dialogues in 7 policy field platforms and in analysis of cross-cutting dimensions (e.g. gender, diversity, ICT), carefully taking into account cross-sector relevance (private, public, civil sectors), and future impact.

Building on theoretical and empirical findings, a foresight methodology will be applied to ensure that conclusions lead to well-grounded policy recommendations, based on attentive analysis of existing innovations.