Transformative entrepreneurs, in contrast to subsistence ones, are a key source of creative destruction and long-run economic growth. However, we still know little empirically about how macroeconomic shocks shape inventors’ entrepreneurial choices as potential transformative founders and their early-stage innovation strategies. In my JMP, I exploit cross-industry exposure to the 2018 U.S.–China trade war, together with a newly constructed, million-scale inventor–firm matched dataset, to study the entrepreneurial consequences of tariffs (a market-size shock) and the Entity List (a negative supply shock). The empirical analysis shows that tariff changes have limited effects, whereas the Entity List induces pronounced two-sided selection in which types of inventors continue to found startups, and leads to substantial reductions in post-entry innovation outcomes. The paper also highlights a new channel through which trade shocks affect innovation at the individual level, rather than only at the firm level.

Do inventor-founded enterprises behave differently from their counterparts? I investigate the large-scale inventor and firm registry database from 2000 in China and develop a Schumpeterian innovation model that explains the difference in their innovation trajectories and provide policy suggestions.

What is the optimal way for organizations to roll out worker–GenAI collaboration? Through field experiments, we reveal a sigmoid adoption path with an early dip and a persistent group of non-adopters. Guided by survey evidence, we build a learning model with learning costs and psychological anchors that generate these patterns and offer intervention strategies for smoother organizational rollout.