Social network analysis to identify actors for participatory food system transformation – Learning from two case studies in Switzerland
Bibliographic Data
| ID | 7473797 |
|---|---|
| Authors | Tobias Geisser (ZHAW Zurich University of Applied Sciences), Alice H Aubert (0000-0001-6613-5942, ZHAW Zurich University of Applied Sciences, corresponding author) |
| Year | 2026 |
| Volume | 123 |
| Pages | 104071 |
| Publication date | 2026-03-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Rural Studies (JOURNAL) |
| Journal identifiers | ISSN: 0743-0167 • E-ISSN: 1873-1392 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.jrurstud.2026.104071 |
| OpenAlex | W7131351866 |
| Language | EN |
| References cited | 28 |
To achieve sustainable food systems, participatory transformation processes are crucial. However, identifying key actors for such processes is challenging. Our study evaluates the use of Social Network Analysis (SNA) in addition to influence-interest matrix and the funnel theory to systematically identify key actors for food system transformation based on two case studies. In both, we compiled a comprehensive list of actors through secondary research and conducted an online survey, which was pre-tested in expert interviews. The survey collected data about the trade, information, and collaboration networks as well as influence-interest matrices of the two selected local milk value chains (Hinwil and Horgen districts located in Switzerland). Results revealed that the SNA did not alter or complement the selection of key actors based on influence-interest matrix or the funnel theory. Thus, despite SNA proving valuable in corroborating actor selection and understanding underlying network structures that might be critical for the participatory transformation processes, we allowed ourselves to question whether it was worth the effort. Indeed, despite simplified design, we faced two main challenges which impacted network completeness, namely low response rates and difficulties in defining system boundaries. Nevertheless, should fellow researchers plan a SNA in future studies, we formulate practical recommendations. • Social network analysis (SNA) compared to influence-interest matrix and funnel theory • Online survey in two Swiss case studies about local dairy systems • SNA corroborated but did not expand key actor identification • SNA revealed structural network features relevant for participatory process • SNA is resource-intensive and should be used selectively
Citizen journalism · Funnel · Key (lock · Network analysis · Process (computing · Selection (genetic algorithm · Social network (sociolinguistics · Social network analysis · Transformation (genetics · Agriculture Sustainability and Environmental Impact · Agriculture, Land Use, Rural Development · Organic Food and Agriculture
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| Citation velocity | historical |
|---|---|
| Highly cited | No |