SEQUOIA: A methodology for the socio-economic impact assessment of Software-as-a-Service and Internet of Services research projects

A methodology for the self-assessment of the socio-economic impact of Software-as-a-Service and Internet of Services research projects is presented in the context of EU-funded research. The SEQUOIA methodology was developed by assessing 30 existing projects in close collaboration with them. This process was documented to provide a basis for future research projects to apply the methodology on their own. The model and the empirical findings are discussed in detail, focussing on five projects that qualified as ‘best practices’. The main findings are that an ‘impact assessment culture’ needs to be cultivated, encouraged, and strengthened by the European Commission and all the stakeholders. The five projects that scored highest generated a fairly good financial return over the total projects’ output lifetime and showed a genuine attention for non-monetizable impacts such as knowledge creation and sharing, improvement in working routines, and social capital. Relative to the other projects, the five best practices demonstrated knowledge of the needs of their stakeholders and of their expectations, and engaged with them from the very beginning of their technology development activities. To integrate the assessment methodology within each project, its partners need to feel that they ‘own’ it, and that it has been optimized for its specific institutional, organizational, and epistemological requirements. We therefore recommend the inclusion in project consortia of socio-economic experts who are able to translate the ICT research language into measurable (potential) socio-economic impacts. SEQUOIA’s assumption that in the development of an effective socio-economic impact assessment methodology it is important to integrate the social and economic dimensions of potential impact was verified and validated through an ex post rationalization informed by economic anthropology, the usefulness of our quantitative model, and empirical evidence obtained through in-depth qualitative–quantitative data gathering techniques.