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Circular economy (CE) is considered a vital model to tackle resource scarcity and reduce waste by promoting strategies that redefine production and consumption systems. Industrial actors integrate CE principles in their strategic and operational practices to overcome these challenges, simultaneously aiming at enhancing their sustainability performance. Despite numerous frameworks to guide organizations in innovating towards CE, very few have embedded explicit sustainability considerations to assist practitioners in understanding the potential sustainability performance of the CE initiatives early in the development process. To assist a structured process of measuring sustainability performance, the main goal of this paper is to propose a procedure for a systematic selection of suitable leading performance indicators to support an informed sustainability-oriented decision-making process. To fulfill this aim, a hypothetical-deductive approach has been followed to, firstly, develop the selection procedure, and secondly, evaluate and improve it using a case study approach. The findings reveal that the procedure enables a systematic selection of relevant indicators by taking into account the manifold combinations of CE strategies and business processes, characteristics of the company and its sustainability objective. Different from many other approaches, the novelty lies in relying on a dynamic, as opposed to ‘prescriptive’, indicator selection process to induce learning about sustainability considerations significant for a particular CE initiative and corporate context.
Early integration of sustainability considerations into decision making is seen as a key enabler for companies to understand the potential implications of their decisions on the triple bottom line aspects. Lack of the tools to support decisions when trade-off between sustainability aspects occur, however, may lead to uninformed decision-making and undesired outcomes. By consolidating the learnings from empirical work together with literature recommendations, we propose key criteria to be considered when developing decision support tools to manage sustainability-related trade-off situations.
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