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Publisher´s version / Útgefin grein ; The core objective of VALUMICS project www.valumics.eu is to develop approaches and tools to analyse the structure, dynamics, resilience and impact of food chains on food security, economic development and the environment. This article presents the work done by the H2020 VALUMICS project during its first year on system dynamics causality-based modelling framework analysis, which has been facilitated through iterative workshops (WS) and group model building. The framework consists of flow charts and causal loop diagrams (CLDs) for supply, value-, and decision- chains for several food supply chains and systems. These are salmon to fillets; beef cattle to steak; dairy cows to milk; wheat to bread and tomatoes to canned tomatoes. The framework will now be further refined with stakeholders from the food value chains, so as to form a consensus vision of the overall system. The outcome will be the basis for the next step in the modelling phase which will focus on parametrisation and operationalising decision rules for the model, in particular with a focus on fairness and distribution of value added in the food supply chain from farmer to the consumers. This work will integrate the learning from the analysis performed in the project in the case studies and includes work on assessment of environmental and social dimension of food chains by life cycle assessment, assessment of transportation, logistics, risk and resilience. A review of policy and governance intervention done by VALUMICS partners will also provide a basis for evaluating governance and power structure in food chains linked to economic studies on food chain organisations, price formation, persistence of supply chain relations, assessment of economies of scale and technical innovations, and a statistical analysis of agribusiness profitability. ; Peer Reviewed

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. CC BY ; Fairness issues within food systems are of increasing concern for policy makers and other stakeholders. Given the topicality and policy relevance of fairness within food systems, there is value in exploring the subject further. Simulation modelling has been successfully used to develop and test policy interventions. However, the subjectivity and intangibleness of fairness perceptions make them difficult to operationalize in a quantitative model. The objective of this study is to facilitate research on fairness in food systems using simulation modelling by defining the social construct of fairness in model operational terms. The operationalization is conducted in two steps. First, the construct of fairness is conceptually defined in terms of its dimensions, antecedents, and consequences using the literature on interorganizational fairness. Then, by focusing specifically on fairness issues within food systems, the conceptual definition is used as a basis for the identification of proxy indicators of fairness. Seven groups of factors related to fairness perceptions were identified during the conceptualization phase: financial outcomes, operational outcomes, power, environmental stability, information sharing, relationship quality, and controls. From these factor groups, five indicators of fairness that are operational in a quantitative model were identified: profit margin as an indicator of distributive fairness and four indicators of procedural fairness related to market power and bargaining power. ; This research was part of the VALUMICS project "Understanding Food Value Chain and Network Dynamics" funded by the European Union's Horizon 2020 research and innovation program, https://valumics.eu/. ; Peer reviewed

Publisher's version (útgefin grein) ; Transitioning agri-food systems towards increased sustainability and resilience requires that attention be paid to sustainable food consumption policies. Policy-making processes often require the engagement and acceptance of key stakeholders. This study analyses stakeholders' solutions for creating sustainable agri-food systems, through interviews with a broad range of stakeholders including food value chain actors, non-governmental organizations, governmental institutions, research institutions and academic experts. The study draws on 38 in-depth, semi-structured interviews conducted in four European countries: France, Iceland, Italy and the UK, as well as three interviews with high-level EU experts. The interviewees' solutions were analysed according to a five-category typology of policy tools, encompassing direct activity regulations, and market-based, knowledge-based, governance and strategic policy tools. Most of the identified solutions were located in the strategic tools category, reflecting shared recognition of the need to integrate food policy to achieve long-term goals. Emerging solutions-those which were most commonly identified among the different national contexts-were then used to derive empirically-grounded and more universally applicable recommendations for the advancement of sustainable food consumption policies. ; The VALUMICS project "Understanding Food Value Chain and Network Dynamics" received funding from the European Union's Horizon 2020 research and innovation programme, under grant agreement No. 727243. https://valumics.eu/. The authors would like to thank the interviewees for their participation in this study, and the two anonymous reviewers for providing useful comments. ; Peer Reviewed

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. ; Peer Reviewed