A Framework for the Selection of Indicators through Fuzzy Thresholds: A Circular Economy Application

The evaluation of indicators has become increasingly important in various domains, necessitating a comprehensive approach to assess their significance and reliability. This paper introduces a novel framework that addresses the challenges of indicators evaluation by incorporating minimum cost consensus (MCC) and fuzzy thresholds. The framework tackles three key issues: experts' preference modeling, the consensus among experts, and acceptance/rejection conditions. By leveraging lin-guistic preferences and the MCC model, the framework generates collectively agreed opinions and manages disagreements whereas fuzzy thresholds account for uncertainty and subjectivity, offering a flexible representation of acceptance criteria. Advantages include closer alignment with experts' thinking, consensual indicators' evaluation, and reliable fuzzy acceptance degrees. Furthermore, the proposal is applied to a circular economy context, demonstrating its effectiveness.