|Title||Social learning in innovation networks: how multisectoral collaborations shape discourses of sustainable agriculture|
|Source||University. Promotor(en): Tom Veldkamp; J.T. Mommaas, co-promotor(en): Kasper Kok. - [S.l.] : S.n. - ISBN 9789461730985 - 182|
|Publication type||Dissertation, internally prepared|
|Keyword(s)||duurzame landbouw - innovaties - innovatie adoptie - sociaal leren - netwerken - discoursanalyse - landgebruik - sustainable agriculture - innovations - innovation adoption - social learning - networks - discourse analysis - land use|
|Categories||Alternative Farming / Agricultural Knowledge Systems|
The increasing complexity of modern day society has led to the emergence of a specific type of sustainability problems known as complex problems. These types of problems can be characterised by their cognitive complexity and inherent insecurity, their normative complexity that allows for completely different interpretations rooted in different worldviews and finally the occurrence of a conflict of interests between different actors.
Sustainable agriculture is the case in point. The Dutch countryside is standing on the threshold of a major transition. Rural development in The Netherlands nowadays involves far more than just restructuring agricultural production. The linear innovation perspective where new knowledge was discovered at universities and subsequently transferred to farmers by means of government sponsored extension services has given way to a new perspective on innovation. This perspective takes a relational view on innovation in which knowledge and innovations are co-created together with stakeholders and it emphasises the importance of experimentation and social learning involving a multisectoral network of actors from science, businesses, government agencies and nongovernmental organisations. The aim of these collaborative innovation networks is to contribute to the transition to sustainable agriculture, a radical and structural change of the agricultural system as a whole.
This thesis focuses on these innovation networks in the context of sustainable agriculture. Its aim is to explore some of the underlying social mechanisms at play in these collaborative networks. Network perspectives have been used extensively to model the linear diffusion of knowledge from universities to farmers and between farmers themselves. However, bottom-up innovation projects with stakeholders do not only require knowledge transfer, but also need to change the organisational structures, laws and institutions governing the sector. This thesis consists of two main parts. The first part of this thesis addresses the content of the concept of sustainable agriculture. It conceptualises innovation as a social learning process in which participants forge new relationships to enhance information flows and learn from each other. The results can thus be divided into ‘outputs’ and ‘outcomes’. Outputs are the plans, scenarios, computer models and indicators that form the physical results of a collaborative process. The outcomes are formed by the building of trust and the development of a new discourse, a new shared language with which to communicate with each other. Using discourse analysis and Q-methodology the existing rurality discourses in the Netherlands were compared to the discourses that were present in the number of innovation projects dealing with sustainable agriculture. Results show that discourses of sustainable agriculture are a natural continuation of existing rurality discourses. The use of technology and the agricultural production function of rural landscapes are among the two most contested elements within the discourses. They are either anti-technological focusing on a multi-functional use of the countryside, or technophile with a strong sense of entitlement of agrarian production in the countryside. Both these extremes are limiting the possibilities for innovative projects to become successful. This thesis defines the concept of Metropolitan Agriculture as a form of sustainable agriculture that combines a technological approach of agriculture on the one hand with a multifunctional use of the countryside.
The second part of the thesis elaborates a new network perspective that links three network functions in innovation systems to individual skills of knowledge creation, institutional entrepreneurship and innovation brokerage. These functions are necessary for the up- and outscaling of a local innovation. Social Network Analysis was used to study the distribution of these three functions over the participants of a collaborative innovation network. Results showed that these three functions are concentrated in three small core-groups and that these core-groups only displayed a very limited overlap. To what extent people are capable to perform one of these three functions depends for a large part on the type of organisation they work for.
Finally, this thesis presents a new mapping technique to investigate and explain the network dynamics of a collaborative innovation network. Using this technique a longitudinal two-mode affiliation network was constructed over a period of 16 years. The analysis of the network dynamics shows how the structural characteristics of size, composition, connectedness and centralisation of a collaborative network change and how these changes are the result of the social relations between actors at the project level as they choose their partners to cooperate with and enter a process of social learning. This thesis therefore shows how the macro-level network dynamics can be explained by micro-level niche processes. It shows how the ideas in the niche change over time with new actors entering the network and other ones leaving after a certain period. The two parts of the thesis together explain how collaboration processes at the niche level can only gradually change societal discourses. In order to ‘sell’ a new idea it has to be embedded within familiar discourse elements. At the same time, these ideas play an important role in finding new partners to collaborate with and expand the existing innovation network.