Modelling the Optimal Testing Strategies for Preventing Wheat Handling Risks

Houtian Ge, James F. Nolan, and Richard S. Gray


simulation, agent-based modelling, optimization, agricultural policy


As a key component of wheat handling in Canadian grain industry, grading of wheat for value-added blending has historically been accomplished by a visual identification method. As of 2008 in Canada, the visual identification was to be eliminated for all primary classes of wheat and replaced by an alternative wheat declaration system. Given the costs of monitoring the trust based declaration system through the wheat supply chain, there exists some potential for accidental or opportunistic misrepresentation behavior under the declaration system on the part of Canadian wheat handlers. This research attempts to identify and measure the risks and costs associated with a functional declaration system. Since the wheat supply chain is characterized by information feedback and heterogeneity among farm agents, identifying optimal testing strategies must be done using economic simulation. An agent-based. An agent-based computational model is developed to capture the effects of individual heterogeneity as well as behavioral adaptation to a declaration system within the extant Canadian wheat handling supply chain. The simulations allow us to identify optimal testing strategies for handlers along with the relative risks and costs associated with each of the testing strategies.

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