Abstract
Because of the need to limit extraction of raw materials and reduce amounts and impacts of waste, countries and businesses are challenged to transition to a circular economy: an economic system in which the materials are reduced, reused, or recycled, but not wasted. Yet, transitioning from a linear to a circular economy implies societal-level, structural changes that have deep implications for existing business models and practices–and the current economic system is still largely organized around virgin material extraction and linear modes of production and consumption. Despite stated ambitions at various geographical scales to become more or fully circular, the outcomes still fall short of such visions. One important reason why the transition towards a circular economy is not proceeding as quickly as hoped can be found in the decision processes used by companies, investors, and policy makers. Suitable frameworks that support decision-making could thus be a key enabler of this transition, if based upon a circular and transformative, rather than a linear optimization logic. In this paper, we therefore explore a different decision-making logic that is developed based on circularity. This provides the basis for an operational framework designed to help decision-makers such as policymakers, investors, and entrepreneurs navigate tradeoffs and take decisions considering the quality of innovation circularity and its respective diffusion potential. To develop, test, and refine our framework—the “Circular Decision-Making Tree”—we synthesized insights from existing frameworks and conceptually integrated these with our understanding of transition theory and the circular economy. We then verified the internal logics and applicability of the framework in a series of usability workshops across four application contexts (Netherlands, Brazil, UK, and South Africa) with feedback from a total of n = 50 stakeholders from policy, practice, and academia. We critically discuss the application potential as well as the limitations and describe implications for future research to further validate the framework’s logics and operationalization.