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The present study is aimed at developing a multi-level framework for assessing circularity in agri-food industries by providing the user with a step-by-step approach and selecting a customized set of indicators capable of accurately assessing the circular economy (CE) level.

The framework is composed of four stages. In the first stage, a CE theoretical model based on operations, product and services, culture, organization and ecosystem criteria has been implemented and adapted to the agri-food sector. In the second stage, users are required to collect a set of indicators capable of measuring each criterion. In the third stage, a weight is assigned to each indicator using analytical hierarchy process (AHP). Lastly, a geometric multi-criteria decision-making (MCDM) model, called axial distance-based aggregated measurement (ADAM) model, is used to normalize, assess and aggregate the results and produce final scores for the different alternatives to be ranked based on their final circularity scores.

The model can be a useful tool to support corporate decisions in the CE, making entrepreneurs aware of their starting level. It indicates the extent to which companies are implementing circular business models across different dimensions and, thus, where they are still lacking.

Beyond the attempts to measure the circularity of corporate performance from a purely environmental perspective, the study adopts a holistic view, considering the complexity and disruption of all the principles of the CE.

Circular supply chains (CSC) are particularly important for the agri-food sector, which faces strict requirements generated by increased food consumption as a consequence of world population growth, changes in lifestyle, development of consumer society and increasing health awareness. Recent disruptive factors have placed the vulnerability of agri-food supply chains in the spotlight. Therefore, the purpose of this paper was to identify the most manageable groups of risks in order to ensure the smooth operation of agri-food circular supply chains.

Seven main risk groups were evaluated in relation to nine criteria. To solve this multi-criteria decision making (MCDM) problem, a novel MCDM model, which integrates the best-worst method (BWM) and the COmprehensive distance-Based RAnking (COBRA) method in a grey environment, was developed.

Three risks were singled out, namely, product features risks, logistics risks and managerial risks. The obtained risks are those whose management would create the most positive effects for the stakeholders and help them achieve their primary goals regarding the circularity of agri-food supply chains.

This study investigates the main characteristics of the CSC in the agri-food sector, identifies, simultaneously explores and ranks all main risk groups associated with them and expands the possibilities for solving these kinds of problems by developing a novel MCDM model. It also identifies the most significant risks, both for individual stakeholders and for all stakeholder groups together.