نبذة مختصرة : The study conceptualizes the ecosystem of an industrial cluster based on circular economy as an umbrella for co-evolving concepts, such as circular economy, cluster economy and industrial ecology (also comprising the concepts of industrial symbiosis and its subcategory, industrial mutualism). We propose an algorithm for estimating the circularity index in an industrial cluster ecosystem as a metric of sustainable ESG performance. The algorithm consists in calculating the integral circularity index of an industrial cluster ecosystem and its inverse, the circular gap. The algorithm developed relies on calculating the estimates for four projections: waste and emissions; consumption efficiency; resource efficiency; investments in environmental protection. We then formulated the key drivers of successful ESG strategies in circular industrial ecosystems, also providing metrics, evidence-based data and measurements of the progress in bridging the circularity gap. We used statistical data available from the Rosstat SDG Platform, Platform for Intelligent Environmental Monitoring, Our World in Data, and Food and Agriculture Organization. The approach was validated for an industrial cluster ecosystem based on the circular economy model, evolving in the Russian Federation from 2012 to 2021. The practical significance of our findings is that the theoretical framework, along with the insights gained and the recommendations developed, can be used for integrating the policies based on sustainable development, environmental management, ESG transformation, circular economy, closed-loop economy for industrial ecosystems. The results obtained can serve for constructing strategies, policies, programs, roadmaps and business models for circular industrial ecosystems at the macro-, meso- and micro-levels.
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