The Role of AI and Digital Ecosystems in Advancing Circular Business Models: A Case Study Perspective

Abstract

Abstract Circular business models are adopted by organizations with the aim to reconcile economic performance with environmental sustainability in response to resource scarcity, regulatory pressure, and growing concerns over waste and emissions. The barrier to mass adoption of circular business models consists of high initial costs and lack of customer demand. Many circular initiatives cannot be scaled beyond pilot stages due to operational complexity, uncertainty concerning quality, and lack of coordination across value chains. Recent studies emphasize the role of digital technologies; however, empirical evidence on the role of artificial intelligence and digital ecosystems in support of circular business models is limited. This study evaluates how artificial intelligence and digital ecosystems enable the implementation and scaling of circular business models based on a qualitative case study of Flip Technologies, a European company which operates an integrated refurbishment and resale ecosystem for consumer electronics. The analysis uses information obtained from a semi-structured interview with senior management and organizational data. The findings indicate that artificial intelligence enhances circular operations by supporting dynamic pricing, automated diagnostics, standardized processes, and the decision-making process, thus reducing uncertainty and improving efficiency. Digital ecosystems also allow for coordination among partners, optimize reverse logistics, and increase transparency and trust across the value chain. Together, these elements improve scalability and economic viability of circular business models. The study contributes empirical insights into circular economy and digital transformation and provides practical implications for organizations looking to scale circular solutions in technology-intensive industries.