Development and evaluation of a taxonomy for platform revenue models

Abstract A critical challenge in launching successful platform business models is the design of viable revenue models. While existing frameworks and taxonomies address platform business models more broadly, conceptual clarity regarding platform revenue models remains limited, particularly in terms of how value is captured among platform actors. The absence of a consistent taxonomy leaves dimensions and characteristics fragmented across studies, thereby constraining theory-building and limiting actionable guidance for managerial decisions on value-capture mechanisms and pricing strategies. This study proposes a taxonomy of platform revenue models comprising 15 dimensions and 64 characteristics. Following a taxonomy design methodology grounded in design science research, we apply iterative design cycles and principles. A controlled experiment is conducted to empirically assess the usefulness of the taxonomy. Our results show that the taxonomy significantly improves the completeness and accuracy of the designed platform revenue models. This research advances platform business model theory by offering an evaluated taxonomy that supports the conceptualization of platform revenue models.