Challenges of operations research practice in agricultural value chains

Abstract

Operations research (OR) methodologies in optimization have been extensively applied to problems in different agricultural value chains in recent years. We take a critical stock take of such applications to date, and reflect on their contribution to value chain sustainability and resilience. The stock take shows that the rate of industry or policy adoption has been limited, partly due to the complex interactions across the segments of agricultural value chains, and the mathematical representation being different to the way the decision maker understands the problem. OR practice in agriculture is also being asked to cover greater spatial scales and engage more stakeholders, and is required to embrace resilience and sustainability objectives. A single-minded focus on optimizing parts of these complex systems without considering the whole system is no longer adequate, and new methods and approaches are required. Complex systems science methods are being applied to analyse the dynamics of complex social–ecological systems, and are starting to find a home in industrial supply chain analysis. We demonstrate how three complex system methods, agent-based modelling, dynamical systems modelling and network analysis, can be applied to agricultural value chains as a means of gaining insights into system dynamics under different and dynamic conditions. The relevance and utility of OR in ensuring the success of agricultural value chains into the future will require practitioners to understand and model value chains as complex adaptive systems.

Keywords:

• agriculture
• practice of OR
• methodology
• complexity

Acknowledgements

The authors thank Dr David Hilbert, Dr Peter Stone, Dr Oswald Marinoni and the anonymous reviewers of Journal of the Operational Research Society for their improvements to earlier versions of this paper.