Abstract

CONTEXTInnovation is an important driver of increased productivity, sustainability and resilience in agriculture, forestry and related sectors. An analysis of how different types of multi-actor co-innovation partnerships function can help to identify the reasons why some are more successful than others in ‘speeding up’ innovation. OBJECTIVETo provide a framework for the analysis of the co-innovation process, we developed a multidimensional conceptual typology of co-innovation activities based on a review of 200 such partnerships involving farmers and foresters from across Europe. This framework is based on innovation systems theory and the prevailing policy context of the ‘multi-actor approach’. METHODSThe overarching concept or dependent variable measured by the typology is ‘effectiveness of co-innovation by a multi-actor partnership’ and the two dimensions of the overarching concept are the ‘structural components of the Organisational Innovation System’, with four categories, and ‘attitude towards interaction’, with two categories. The result is a matrix of eight ‘ideal types’ of co-innovation activity. These eight types are characterised according to first-order constructs derived from our research data. RESULTS AND CONCLUSIONSThe results show that the co-innovation process can successfully take contrasting forms according to the ‘contextual contingencies’ encountered by the partnership. In other words, no one ideal type is intrinsically ‘superior’ to another but may be more ‘appropriate’ in given circumstances. Factors influencing approaches to implementation include actor capacities, aspirations and networks, the co-innovation topic and its influence on the partnership size and the workplan structure, the type of co-innovation activity outputs and the need to engage with the ‘larger periphery’ of stakeholders, and the nature of the enabling environment. SIGNIFICANCEThe typology is not a classification since the ideal types represent organisational forms that might exist rather than real partnerships. However, the analytical framework it provides will help policy makers and programme managers to develop targeted interventions, according to actor needs and local circumstances, for ‘speeding up’ innovation.

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