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Abstract
Agri-food chains are complex systems involving multiple multifaceted firms usually working
together within specific industry sectors (e.g. grains, beef, wool, dairy) to satisfy an increasingly
globalised market demand for high value food products. In so doing, the groupings of companies
involved in an agri-food chain undertake activities that require multidimensional inter-organisational
and cross organisational decision-making in the process of adding value to a raw
commodity product through the production, manufacturing and distribution stages of the chain.
Additional complexity is added by climate variability which impacts randomly and unpredictably
on decision making in every component of the chain.
The work outlined in this paper is a pilot investigation looking at a number of approaches to
conceptualising and modelling an agri-food chain and its related decision making processes to
better evaluate the impact and effects of that decision making and associated information flows
across the components of the agri-food chains. The modelling approaches were (i) a multimedia
model initially explored as an opportunity to visualise supply and value chain issues for educational
purposes; (ii) an agent based model (ABM) using deterministic rules to architecturally
synthesise a supply chain, and (iii) a baysian belief network (BBN) which we discuss as an approach
for looking at the likelihood of certain decisions being made under certain scenarios.