Analysing price volatility in agricultural value chains using systems thinking: A case study of the Indonesian chilli value chain

Abstract CONTEXT High price volatility in agricultural commodities can be a major issue for value chain actors exposed to its adverse economic impacts. Price volatility results from the interaction of multiple factors linked within dynamic and complex agricultural systems. Therefore, to address price volatility, the approach needs to be capable of analysing feedback that occurs in such complex systems. OBJECTIVE We integrate a systems thinking approach and value chain analysis to overcome the constraint of other methods to explicitly describe and understand how system structure influences system behaviour observed in price volatility and the assessment of the consequences of ex-ante and ex-post policy interventions based on this understanding. METHODS The proposed integrated approach involves the active participation of value chain actors and stakeholders to improve their understanding of the complex systems they operate within including the policy environment. The approach takes the Indonesian chilli value chain as a case study. We implemented the first two steps of systems thinking (i.e., articulating problems and formulating dynamic hypotheses). In the group model building processes, we developed causal loop diagrams to represent a dynamic hypothesis that explains the feedback loops that cause price oscillation behaviour and systems archetypes that identify potential intervention points. RESULTS and CONCLUSIONS The integrated approach was able to link the Indonesian chilli value chain's system structure and the system behaviour observed in price volatility. The causal loop diagram clearly displays the feedback between production, market governance, consumption, and price. The diagram also portrays how these factors impact value chain actors' performance and the influence of time delays and random shocks on the entire value chain system. Limits to growth and shifting the burden archetypes were identified as critical leverage points in formulating fundamental policy interventions to address price volatility. SIGNIFICANCE This study demonstrates the strengths of the proposed approach in developing a comprehensive dynamic qualitative model of a whole value chain system that influences the system behaviour, such as oscillation, which other modelling studies do not consider. The use of system archetypes to identify intervention points is another research contribution in that it improves value chain analysis. The results also highlight the benefits of participatory system dynamics modelling in enhancing the learning of value chain actors in anticipating the consequences of any actions or random shocks on the entire systems.