Innovation Shocks and Knowledge Creation of Emerging Technologies: Evidence from a Quasi-Experiment

This study explores how innovation shocks – sudden and exogenous breakthrough events – shape the evolution of emerging technologies by influencing the knowledge creation of individuals. Drawing on the literature on technological evolution and the conceptualization of knowledge creation as recombinant process essentially at the individual level, we argue that innovation shocks stimulate knowledge creation as their generic nature bridges nascent technologies with individuals’ existing knowledge and experiences, enabling better search for components and configurations compatible with emerging technologies. Our empirical examination exploits an exogenous innovation shock in artificial intelligence - the winning of deep learning algorithm AlphaGo over Go grandmaster Lee Sedol in 2016. The analyses of coding activities of developers on GitHub reveals their knowledge creation of deep learning projects significantly increased after the winning, compared with that of blockchain - another influential emerging technology unaffected by any innovation shocks during the same period - providing causal evidence supporting our theory. Moreover, we found this positive effect of innovation shocks on knowledge creation is enhanced by developers’ absorptive capacity and knowledge scope. This study advances the understanding of individual dynamics in the evolution of emerging technologies and the impact of artificial intelligence in creating new forms of innovation.