Modelling Drivers and Barriers to Circular Trade Between the United Kingdom and European Union in the Agri-Food Sector: A Systems Thinking Approach

Angelica Nahalka^*Luiza Toma

• Scotland's Rural College, Edinburgh, United Kingdom

The circular economy has gained increased attention as an actionable framework for creating more sustainable economic systems that reduce waste and pollution. Often excluded from discussions of circular economy is international trade and circular economy applications in the agri-food sector, despite their significant climactic impact and evidence for increased circularity potential. The trade relationship between the United Kingdom (UK) and European Union (EU) offers a unique case study for investigating drivers and barriers to greater circularity in international agri-foods trade. Though both parties have voiced commitments to fostering circularity into their respective economic systems, few concrete measures to promote circular trade have been considered between the UK and EU. In this paper, a literature review was conducted to establish a definition of circular trade as it relates to agri-food sector activity and propose ways to increase circularity in this case study. A combined literature review and systems thinking approach was used to model drivers and barriers to circular trade in the case study context via causal loop diagrams. This study found that policy-based interventions at multiple levels, from international to nation-level regulations and policy, should be leveraged to facilitate circularity of trade by increasing ease of performing circular trade activities. This includes adapting intellectual property rights legislation to better facilitate reuse and repair activities and harmonizing key definitions and procedures to increase reciprocity of goods and services to better enable reuse and repair activities inherent to circular activities. Further research should aim to refine best practices in circular trade within agri-foods as there is currently a gap in quantitative data to inform optimal circular value chain activities.