Please use this identifier to cite or link to this item: http://hdl.handle.net/2307/5234
Title: Transitions to sustainable socio-technical regimes in organic agriculture
Authors: Ortolani, Livia
Keywords: social network analysis
organic agriculture
transition theory innovation
sustainability
Issue Date: 19-Jun-2015
Publisher: Università degli studi Roma Tre
Abstract: According to the literature on regime transition, niches are sources of innovation that may lead to the transformation of the dominant regime, if processes at other level of the system – the landscape and the mainstream regime - are supportive (Loorbach and Rotmans, 2006). A focus on actors involved in the transition process and the analysis of their specific role in knowledge networks can help assessing the robustness of a specific niche and its growth potential (Hoogma et al. 2002). Knowledge systems, and in particular the dynamics of local and expert knowledge, have in fact a key role in innovation models. Different trajectories characterize the transition process, leading to different results: from co-optation and gain in efficiency of the mainstream regime to its radical transformation. This research integrate transition theory with actor network theory and ego network analysis to conduct an in-depth analysis of six case studies of entrepreneurs in three EU countries. Organic farming is used as an example of radical innovation in agriculture that had a long term and diversified shift from niche innovation to regime practice. Relational data were collected using participative methods, then analysed in order to understand how the six organic farms' transition trajectories can be defined and characterized from a multilevel perspective. The analysis of each farm organisational model, using goods and money ego networks gave indication of each farmer vision of sustainability. The main assumption is that leading actors in the farms' knowledge networks will influence a specific transition trajectory, shaping its direction and transformative potential. Three main trajectories were identified on the basis of the analysis of farms' knowledge networks, and the position of each farm was analysed taking into account the dynamic nature of the transition process.
URI: http://hdl.handle.net/2307/5234
Access Rights: info:eu-repo/semantics/openAccess
Appears in Collections:Dipartimento di Economia
T - Tesi di dottorato

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