Navigating dead ends: the role of organization-level search strategies in general-purpose technology ecosystems

The development of emerging General-Purpose Technologies (GPTs) is fraught with uncertainty, particularly in identifying promising knowledge recombinations and application areas. Technological progress can stall when firms, universities, and independent inventors pursue “dead ends” in their search strategies, disrupting the trajectory of follow-up innovations. While prior research has largely examined GPT evolution at a macro level, this study investigates how organizational search strategies influence these trajectories. Focusing on Wearable Haptics Technology (WHT) as an emerging GPT, we analyze 1,261 patent-applicant pairs to explore the impact of knowledge recombination strategies. Our findings reveal that patents exploring entirely new technological domains are less likely to catalyze follow-up inventions. In contrast, patents that incorporate novel knowledge within the existing WHT ecosystem are more likely to drive subsequent innovation. A supplementary analysis further shows that university involvement is more beneficial in explorative and domain-pushing projects than in exploitative ones. Our findings contribute to research on entrepreneurial ecosystems by clarifying how different actors and search strategies shape knowledge dynamics in early-stage GPTs.