Although the circular economy (CE) concept is gaining traction and methods to assess companies’ CE-related aspects exist, there is no established CE assessment tool. In many cases, it is not clear how metrics or indicators included in extant CE assessment methods have been selected. To fill this gap, this paper presents a new instrument named Circularity and Maturity Firm-Level Assessment tool (CM-FLAT). The CM-FLAT has been developed starting from a transparent scientific basis, i.e., a recent systematic literature review and comprehensive collection of CE metrics. In addition, it targets the separate assessment of CE maturity, i.e., the presence of documented activities and practices laying the foundations for CE introduction, and circularity, i.e., attained CE-related performances. The development of the CM-FLAT has foreseen its formal evaluation by experts in the field of CE and sustainability, and its testing by a pilot group of companies from South Tyrol, Italy. The multiple verification activities have confirmed its usefulness and usability. Therefore, companies can now benefit from a tool capable of providing a comprehensive framework of factors and organizational areas affecting the introduction of the CE. This will be fostered by a computer-supported tool implementing the CM-FLAT, which represents the authors’ future work.

Smart Agriculture (SA) is an evolution of Precision Farming (PF). It has technological basis very close to the paradigms of Industry 4.0 (Ind-4.0), so that it is also often referred to as Agriculture 4.0. After the proposal of a brief historical examination that provides a conceptual frame to the above terms, the common aspects of SA and Ind-4.0 are analyzed. These are primarily to be found in the cognitive approaches of Knowledge Management 4.0 (KM4.0, the actual theoretical basis of Ind-4.0), which underlines the need to use Integrated Information Systems (IIS) to manage all the activity areas of any production system. Based upon an infological approach, “raw data” becomes “information” only when useful to (or actually used in) a decision-making process. Thus, an IIS must be always designed according to such a view, and KM4.0 conditions the way of collecting and processing data on farms, together with the “information precision” by which the production system is managed. Such precision needs, on their turn, depend on the hierarchical level and the “Macrodomain of Prevailing Interest” (MPI) related to each decision, where the latter identifies a predominant viewpoint through which a system can be analyzed according to a prevailing purpose. Four main MPIs are here proposed: (1) physical and chemical, (2) biological and ecological, (3) productive and hierarchical, and (4) economic and social. In each MPI, the quality of the knowledge depends on the cognitive level and the maturity of the methodological approaches there achieved. The reliability of information tends to decrease from the first to the fourth MPI; lower the reliability, larger the tolerance margins that a measurement systems must ensure. Some practical examples are then discussed, taking into account some IIS-monitoring solutions of increasing complexity in relation to information integration needs and related data fusion approaches. The analysis concludes with the proposal of new operational indications for the verification and certification of the reliability of the information on the entire decision-making chain.

In a world that seeks to reduce the environmental impact of urban areas and implement the Circular Economy, governance is seen as a key to the ecological transition and the achievement of Sustainable Development Goals. How can we use data, knowledge, and resources at our disposal to put into practice a governance model that implements the Circular Economy of territories? This study devised this model. The comparative assessment of enablers and barriers presented in the literature review conducted allowed for the categorisation of indicators related to the literature sample, leading to the creation of a “Territory Circularity Index” composed of four thematic areas. The index was then incorporated into an innovative governance model intended to serve as a practical tool for local governments and policy makers. In the context of the Circular Economy and Sustainable Development, a “Flexible Governance Model” tailored to the territory could effectively contribute to the creation of coherent policies, an open and transparent process, and facilitated consultation with local stakeholders. The evaluation of the results indicates the potential of the “Flexible Governance Model for a Territory Circularity Index” in promoting effective mechanisms for implementing the circular economy, based on the dual quantitative and qualitative approach from which the model originated. The research could be particularly important for various stakeholders: researchers, policy makers, entrepreneurs, and governments.