Abstract

Value chain analysis has been widely used as a diagnostic approach to identify and address complex issues across value chains in an agricultural development context. While comprehensive, the method is primarily qualitative and static in nature, it has limited capability in capturing the dynamic interactions between components from production to consumption and their linkages within a complex system. The application of system dynamics in value chain analysis has the potential to address the limitations. We conducted a systematic literature review to synthesise the underlying reasons behind the application of system dynamics in value chain analysis and understand how it has been operationalised. Results show that the primary reasons why system dynamics is used in value chain analysis were improved ability in capturing the feedbacks, dynamic behaviours and time delays, modelling the dynamics of governance and roles of support systems over time, incorporating multiple causal factors, and measuring performance and policy interventions over time. This can be broadly attributed to the need to improve the analytical rigour of value chain analysis. The applications of system dynamics in value chain analysis varied according to the agricultural commodities analysed, the modelling process followed, dynamic complexity modelled, and the scope of the value chain components analysed. We discuss the contributions, limitations, and opportunities for future improvements. A preliminary framework is proposed to improve the application of system dynamics in value chain analysis.

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