Abstract
System dynamics and agent-based simulation modelling approaches have a potential as tools to evaluate the impact of policy related decision making in food value chains. The context is that a food value chain involves flows of multiple products, financial flows and decision making among the food value chain players. Each decision may be viewed from the level of independent actors, each with their own motivations and agenda, but responding to externalities and to the behaviours of other actors. The focus is to show how simulation modelling can be applied to problems such as fairness and power asymmetries in European food value chains by evaluating the outcome of interventions in terms of relevant operational indicators of interorganisational fairness (e.g., profit distribution, market power, bargaining power). The main concepts of system dynamics and agent-based modelling are introduced and the applicability of a hybrid of these methods to food value chains is justified. This approach is outlined as a research agenda, and it is demonstrated how cognitive maps can help in the initial conceptual model building when implemented for specific food value chains studied in the EU Horizon 2020 VALUMICS project. The French wheat to bread chain has many characteristics of food value chains in general and is applied as an example to formulate a model that can be extended to capture the functioning of European FVCs. This work is to be further progressed in a subsequent stream of research for the other food value chain case studies with different governance modes and market organisation, in particular, farmed salmon to fillet, dairy cows to milk and raw tomato to processed tomato.
Highlights
A food system constitutes a series of actors performing activities and making decisions involved in bringing products from primary production, through processing and distribution to the final consumer [1]
There seems to be a shortage in the literature of research that considers hybrid system dynamics & agent-based models of the whole food supply chain, from producers to consumers, thereby incorporating the full extent of interaction and feedback within the chain; one contribution of this paper is to address this gap in the literature
We have illustrated how techniques such as cognitive mapping can be used for system analysis and conceptual modelling of the fairness problem and argued that a hybrid system dynamics and agent-based model is appropriate for representing Food Value Chains (FVCs) and fairness insights from the model conceptualisation, i.e., the cognitive and agent maps, as well as the longer-term goal of this stream of research, i.e., to explore how this conceptual model can be formulated quantitatively in terms of equations and algorithms and implemented and validated as a policy scenario simulator for policy experimentation and optional recommendations
Summary
A food system constitutes a series of actors performing activities and making decisions involved in bringing products from primary production, through processing and distribution to the final consumer [1]. Food system transformation highly depends on the collaboration and cooperation of FVC actors which is where the issue of fairness plays an important role since actors are less likely to collaborate and coordinate activities when they perceive themselves to be impacted by unfair trading practices (UTPs) [8]. Earlier findings have indicated that the negative impact of unfair trading practices on small and medium size enterprises (SMEs) in the EU food sector is affecting the competitiveness of the industry [9]. Another topic of concern is the effect of EU competition law on collaborative practices which has been identified to be a barrier to collaborative sustainability initiatives in food value chains [10]
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