Mapping the Future of EU Agriculture: A System-Based Assessment of Technological Impacts Using Generalised Fuzzy Cognitive Maps
Keywords
Loading...
Authors
Issue Date
2025-07-07
Language
en
Document type
Journal Title
Journal ISSN
Volume Title
Publisher
Title
ISSN
Volume
Issue
Startpage
Endpage
DOI
Abstract
This thesis explores how the EU agri-food system may change under different levels of technological adoption, focusing on productivity, economic performance, and environmental sustainability. Using Generalised Fuzzy Cognitive Mapping (GFCM), two future scenarios were simulated: one with widespread use of new plant breeding technologies (Scenario 1: Plantovation), and one where such technologies were mostly excluded (Scenario 2: REJECTech). The results show that Scenario 1 led to clear improvements in crop yield, resilience, and ecosystem services, with more consistent model outcomes. In contrast, Scenario 2 produced few changes, with the system behaving similarly to the baseline. Productivity-related variables responded most strongly to technological change, while economic variables remained largely stable across all scenarios. This stability reflects both their position in the model and the fact that economic outcomes are more influenced by long-term policy and market factors than by innovation alone. Overall, the study finds that technological innovation can improve sustainability and productivity, but economic transformation requires broader structural changes. Therefore, combining innovation with supportive policies offers the most effective approach to strengthening the EU agri-food system.
Description
Citation
Supervisor
Faculty
Faculteit der Managementwetenschappen