Food Supply Chains and Eva.CAN Model: a Network Analytic Approach

The research work leading to the drafting of this PhD thesis approaches the analysis of supply chains of products of animal origin from various productive species by using network analytic methods. In the studied analysis six supply chains are embedded in a single model which highlights all the interconnections that have little evidence in traditional models. This new model that we called Eva.CAN (Evaluation of Complex Agri-food Network Model) is a new concept model, the first complex network model for the agri-food production, the first to allow the application of Network Theory analysis methods. The initial hypothesis is that the various supply chains of products of animal origin have to be interpreted and analyzed as a whole, as a single complex system. The complex network is studied analyzing the adjacency matrix that constitutes the network with algorithms and methods extensively tested and validated. This analytical approach has already been applied with positive results in many research areas such as social networks, transport networks, the stylistic of writers and musicians, proteomics, pharmacology, medicine, biology, and many others. We apply this methodology to supply chains of products of animal origin and show a series of preliminary results. This method of study of food supply chains could be useful for an observatory, bringing to light slightly evident relations and becoming a strong support for policy-makers. It can also provide useful advices to individual actors on how to optimize their own supply chains. Finally, through an effective enumeration and evaluation of the relationships, a network model could be helpful in design of tracking and traceability systems.