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Resilience of Agricultural Supply: The Impact of Climate Change on Optimal Seed Production and Allocation

Journal Article
Agricultural supply chains have have been experiencing an increasing number of disruptions due to natural disasters, extreme weather events, geopolitical disturbances, and animal or plant diseases, amplifying concerns about the resilience of food supply. This paper focuses on the supply of commercial seeds, the key input into agricultural supply chains. The authors examine how supply chain disruptions affect the optimal production decisions of seed manufacturers, the expected revenue of farmers that are part of the production process, and the resilience of food supply. They model the seed production process as a discrete-time stochastic dynamic optimization problem where, in each period, the seed manufacturer solves an optimization problem with two stages: The planting stage, where the manufacturer chooses the quantity of hybrid seeds to produce through a network of independent farmers, and the allocation stage, where the manufacturer allocates the resulting yield to different markets with varying profit margins. They then examine how changes in the likelihood of a disruptive event affect the supply chain’s performance. They prove that, as the probability of disruption increases, (a) the manufacturer’s expected profits decrease while the optimal planting quantity grows; (b) the expected total yield decreases, reducing the expected profit of the farmers who are under contract with the manufacturer; (c) the expected allocation quantity to different markets decreases with a more significant drop in smallholder markets. Finally, they present a simulation model calibrated to industry data where they find that even a small increase in the likelihood of supply volatility can dramatically change the optimal production decisions and have significantly negative effects on the profitability of commercial seeds, on the availability of seeds in smallholder markets, on the profits earned by contacted farmers, and on the value of typical operational improvements such as delayed differentiation.
Faculty

Professor of Operations Management