Dynamic system evaluation of fluctuating processor raw material on value chain financial sustainability

Abstract

As the global population grows, food self-sufficiency in developing countries becomes increasingly important and difficult (FAO, 2023). Due to variables like weather, agricultural production remains volatile, providing processors with an inconsistent supply of raw materials, making it difficult to operate at a reliable and sustainable utilisation and supply food consistently and competitively in the global market.

This project aimed to evaluate the impact of a change in available raw material volume at the processing node on the total value chain’s financial sustainability. The project’s goal included illustrating and measuring the effect of seed availability, as well as determining the ideal amount of seed to be processed for maximum value chain financial sustainability. This was done with a system dynamic model that represented the Tanzanian sunflower value chain, including producers, traders and processors and measured financial sustainability with the net income indicator. Steps to develop the system dynamic model included the problem and background articulation, dynamic hypothesis with the causal loop diagram development, the mathematical formulation in AnyLogic, model verification and validation, and scenario analysis. The developed model represented the Tanzanian sunflower value chain accurately and assisted in gaining insight into managing different raw material availability disruptions (increasing and decreasing seed availability by 10% to 50%), which quantified the impact on each node’s financial sustainability with the net income indicator. This illustrated the efficiency gains due to economies of scale and supply and demand price trade-offs. Furthermore, a significant scientific contribution was to optimise the entire value chain to maximise the total value chain net income by determining the ideal amount of seed to be processed.

The results illustrated how the model could contribute to quantifying a variety of different scenarios to analyse the impact of different interventions on the entire value chain system. The model quantified the financial sustainability of the value chain, however, as with most research, the model can be further improved to refine the results and incorporate different performance indicators (like environmental and governance) which may widen the reach of the results.