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Tropentag, September 14 - 16, 2022, Prague

"Can agroecological farming feed the world? Farmers' and academia's views."

Emergent participatory scenario analysis (E- PaSA) as framework for foresight analysis in food systems

Joshua Aboah

ILRI, Joshua aboah, Ghana


Leverage points (LPs) are pathways in complex systems where small alterations can create cascaded changes in the whole system. Although LPs are the building blocks for scenario planning; LPs are not intuitive. Yet, LPs have mostly been qualitatively and subjectively determined. Moreover, the hierarchical nature of LPs requires a quantitative assessment to ascertain the potential impact of intervention scenarios drawn from them. Indeed, some interventions are not sustainable because they either target weak LPs instead of the most impactful LPs, or the unintended consequences of the interventions are not considered. To bridge this gap, the Emergent Participatory Scenario Analysis (E-PaSA) is presented as a framework that can support the integration of LPs and scenario analyses in food systems.
The E-PaSA framework involves three phases. Phase 1 involves the integration of qualitative and quantitative system dynamics (SD) modelling procedures. The system is mapped out using a causal loop diagram to capture the causal relationship among variables that shape the system structure and behaviour and to highlight the inherent feedback in the system. The causal loop diagram is then translated into a quantifiable model, which is simulated to determine the baseline levels of key indicators and the dominant feedback loops.
Phase 2 consists of the formulation of scenario objectives based on the dominant feedback loops identified in Phase 1. The objectives are presented to a reference group to brainstorm plausible intervention scenarios to achieve the scenario objectives. The interventions are linked to specific system parameters, and the consistency of the intervention scenarios is tested by comparing the causal relationship among the identified parameters.
In Phase 3, the alterable parameters are used to revise the system structure, and the revised model is simulated. Results from the simulation runs are compared to determine the impact of each intervention scenario. Finally, the statistical significance of the impacts is estimated to determine the threshold of impact.
The uniqueness of the E-PaSA is that unlike other methods for developing dynamic scenarios that begin with a pre-modelling phase where scenarios are qualitatively determined E-PaSA begins with a modelling phase to determine the leverage points for scenario development.

Keywords: Food systems, leverage points, scenarios, system dynamics modelling

Contact Address: Joshua Aboah, ILRI, Joshua aboah, P.O. Box Co 306, 233GH Accra, Ghana, e-mail: j.aboah@cgiar.org

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