Research
Research
This paper studies how acquirers with AI-equipped teams perform on target selection, deal efficiency, synergy realization, and innovation. AI-adopting acquirers expand their search radius on target candidates to less similar industries and more distant locations. Post AI-adoption acquirers reduce headcounts in M&A teams yet initiate more deals, and reduce the duration to deal closure. These acquirers enjoy higher synergies by product differentiation and preempting competitive threats. Finally, these acquirers improve post-merger innovation performance, as evidenced by filed patents.
(With Tetyana Balyuk)
We study how e-commerce affects credit provided to small businesses in the U.S. Theoretical predictions are ambiguous as e-commerce can affect credit supply and demand in opposite directions. We find that small businesses have higher sales, larger orders, and more stable revenue after e-commerce adoption, suggesting that online sales are more efficient than offline trade. Lower cash flow volatility should reduce credit demand, because small businesses often borrow to finance liquidity shortfalls. Yet, we find that businesses obtain more credit after e-commerce adoption, even after controlling for higher efficiency. We confirm these findings using the staggered entry of Uber Eats in the food industry and other strategies. Our results are consistent with e-commerce relieving credit constraints both directly by increasing expected payoffs to lenders due to higher sales and indirectly by lowering lending costs due to hard data generated in e-commerce. We also find redistributional effects of e-commerce on credit across industries in local credit markets.
This paper examines how AI shapes productivity and creativity in innovation. Using a matched dataset that links patent records with labor data from 2005 to 2024, I find that AI-exposed inventors and their affiliated firms are more productive and generate patents that are more explorative, span broader technological domains, and are more customized to firm-specific needs. However, their patents are not less textually similar to prior art. Heterogeneity analyses reveal that these effects vary between AI developers and AI users, implying role-based differences across inventors.
(Work in progress)
Presented at: Goizueta Doctoral Research Conference (2025)