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Measuring the circular economy - A Multiple Correspondence Analysis of 63 metrics
- Parchomenko, Alexej, Nelen, Dirk, Gillabel, Jeroen, Rechberger, Helmut
- Journal of cleaner production 2019 v.210 pp. 200-216
- circular economy, correspondence analysis, longevity, monitoring, recycling
- Considerable efforts are undertaken to make the transition towards a more Circular Economy (CE). At the same time there is no generally accepted monitoring framework. Rather, what exists is a large variety of measurement approaches that aim to assess the progress. The different assessment methodologies cover different and varied aspects of the CE transition and are seemingly unrelated to each other. Therefore, the main contribution of this paper is the provision of a structured picture of the current stock of CE metrics, including the identification of methodology clusters and the related assessment perspectives. The method of Multiple Correspondence Analysis (MCA) was used to assess 63 CE metrics and 24 features relevant to CE, such as recycling efficiency, longevity and stock availability. The MCA was used to assess how the different CE features are associated to each other and how they are related with each of the 63 metrics. Also, it was determined which combinations of CE features are frequently assessed together. The analysis identified three main clusters of metrics, (1) a resource-efficiency cluster, (2) a materials stocks and flows cluster, (3) a product-centric cluster. The results of the analysis show poor integration of resource-efficiency and product-centric perspectives, while the product-centric and system-dynamic perspectives are least frequently assessed. Further, the analysis provides the most prevailing CE perspectives and it is shown that only a few CE metrics assess CE features that are related to the maintenance of value. The MCA provides a guidance for further metrics development, as it identifies areas with a lower metrics density. For a detailed analysis, a standardized visualisation framework for CE metrics is derived, which allows to compare individual metrics in a simple and illustrative way. The goal of the visualisation framework is to provide guidance for (i) the integration of the most complementary CE metrics and (ii) facilitate further metrics development.