Structure of Data-Driven Business Models for the Circular Automotive Sector: A Taxonomy

Companies in the automotive sector are under increasing pressure from stricter regulations, shifting customer expectations, and ambitious sustainability goals. The circular economy (CE) provides a promising pathway to address these challenges by promoting resource efficiency, lifecycle extension, and closed material loops. Meanwhile, data-driven business models (DDBM) enable enhanced transparency, optimization, and innovative value creation through digital technologies (DT). While the integration of circular strategies and data-driven approaches has significant transformative potential, circular DDBMs remain scarce in the automotive industry and lack systematic conceptualization. To address this gap, this study develops a taxonomy that structures the current landscape of circular DDBMs using a rigorous, iterative methodology. The resulting taxonomy, based on 42 empirical cases, comprises six meta-dimensions, 16 dimensions, and 68 characteristics, offering a comprehensive framework for analyzing, comparing, and designing circular DDBMs in the automotive sector.