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The development and application of appropriate Circular Economy indicators is an issue that concerns both the scientific and the business community, as well as decision makers. The existing gap between research, policy and practice could be bridged by using a dynamic indicators selection approach that combines both expert and participatory practices. This study aims to develop such a novel approach for the selection of indicators based on views and needs of practitioners, whilst considering the complex interdependencies of the indicators and determining their importance. Twenty circularity indicators for the Water-Energy-Food-Ecosystems nexus are selected and ranked by different stakeholders. The interrelationships of the indicators are identified using the Interpretive Structural Model, resulting in six levels of importance. Cross-impact matrix multiplication applied to classification (MICMAC) analysis further enabled the classification of the twenty indicators into four categories based on their driving and dependence power. The results indicate that seven indicators—one related to regeneration of natural environment principle, four related to keep resources in use, and two related to design out negative externalities—are the driving indicators to Circular Economy. The approach can be applied to other sets of indicators as well, enabling their prioritization and implementation with other systems.

Validating Circular Performance Indicators: The Interface between Circular Economy and Stakeholders