A design science approach to scaling platform business models

Platform business models are central to the digital economy, yet few achieve sustainable scaling—exponential expansion combined with resource-efficient value creation. Existing research highlights the role of business model design choices and managerial agency in shaping scaling outcomes but offers limited insight into how scalable configurations are generated under uncertainty. We address this question by adopting a design science perspective on platform scaling. A multi-case study of four platforms transitioning from two-sided markets to complex ecosystems reveals how firms generated scaling solutions through blending—the recursive recombination of business model ingredients across industries and geographies. This process was guided by scaling intentions and reinforced through immersion in the digital economy, enabling firms to construct and progressively stabilize novel configurations while shaping ecosystem interdependencies. Over time, recurring patterns in these design practices were codified into simple rules that guided subsequent scaling efforts. These insights contribute to research on platform scaling by shifting attention from identifying effective configurations to explaining how such configurations were generated under uncertainty. They further advance research on heuristics by reconceptualizing simple rules as generative principles that emerge from situated design processes, and extend design science by providing empirical insight into how such processes unfold in established platform firms.