The language of co-creation has become popular with policy makers, researchers and consultants wanting to support evidence-based change. However, there is little agreement about what features a research or consultancy project must have for peers to recognise the project as co-creative, and therefore for it to contribute to the growing body of practice and theory under that heading. This means that scholars and practitioners do not have a shared basis for critical reflection, improving practice and debating ethics, legitimacy and quality.
In this paper, presented at the 8th European IFSA Symposium ( Workshop 6: "Change in knowledge systems and extension services: Role of the new actors") in 2008, the authors discuss a conceptual framework that understands innovation processes as the outcome of collaborative networks where information is exchanged and learning processes happen. They argue that technical and economic factors used to analyse drivers and barriers alone are not sufficient to understand innovation processes.
In this chapter the authors compute measures of total factor productivity (TFP) growth for developing countries and then contrast TFP growth with technological capital indexes. In developing these indexes, the authors incorporate schooling capital to yield two new indexes: Invention-Innovation Capital and Technology Mastery. They find that TFP performance is strongly related to technological capital and that technological capital is required for TFP and cost reduction growth.
The timeline tool is generally put to use when stakeholders embark upon the self-assessment phase of their innovation partnership. Stakeholders are asked to recall moments they feel were significant for the partnership, from its beginning to the present and to reflect upon how the partnership has evolved since it began.
Social Network Analysis is a practical and useful tool that looks at the linkages present in an innovation network and monitors their development over time. It maps the relationships between the stakeholders in the network and highlights the changes between them.
This tool enables participants to become cognisant of the functional capacities discovered through the capacity scoring questionnaire, and test the limits of these capacities through simulations or role-playing (e.g. problem-solving, collaboration, information sharing, and engagement). The simulation game leads to an intuitive understanding of innovation capacities and of the importance of the enabling environment, helping participants to learn about the significance of these capacities.
This tool was designed to assess innovation capacities, identify strengths and weaknesses and monitor capacity changes over time. The scoring tool makes it clear which functional capacities are going to be needed to promote, lead or successfully participate in innovation processes. The tool evaluates capacities on the basis of 21 indicators (each of which is graded on a scale from 0 (low capacity) to 3 (high capacity), and build on the key innovation capacities identified in the capacity needs assessment.
The scoping study explores the nature and dynamics of the agricultural innovation system in order to disclose past and ongoing investments and mechanisms relating to AIS in the country. In particular, the study looks into the various initiatives and projects that support capacity development processes.
This tool is a simple tool to map out the current status of the AIS, and to discover where the actors want to go. The rich picture tool can be used both to describe the current situation and to illustrate future plans. A rich picture opens up discussions and helps participants reach a broad and collective understanding of the situation.
The capacity-focused problem tree pinpoints a core capacity issue, along with its causes and effects. It helps clarify the precise capacity-development objectives that the intervention aims to achieve. The focus should be on functional capacity, but room should be left to acknowledge technical capacity issues too.