AI Innovation and Firm Performance in the Medical Device Industry

📅 2026-09-08
📈 Citations: 0
Influential: 0
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🤖 AI Summary
研究通过结合FDA许可、专利等数据,探讨了AI创新对医疗器械公司绩效的影响,发现外部AI研究合作尤其是与产业和临床的合作能有效促进AI设备引入并提高劳动生产率。
📝 Abstract
Whether artificial intelligence pays off for the firms that build it into their products is hard to establish, because AI innovation is itself hard to observe. The medical technology sector is a rare exception: an AI-enabled device must obtain clearance from a national health authority before it can reach a patient, leaving a dated, firm-attributable record of AI innovation output that can be observed directly rather than proxied. We exploit this setting with a three-stage recursive model estimated on a novel firm-level dataset linking FDA premarket clearances, USPTO patents, Scopus publications, and Orbis financials, tracing the full innovation chain from external collaboration through AI device introduction to firm performance. We find that external AI research collaboration is a robust driver of AI device introduction across firm sizes and estimators, with a larger effect for small firms, consistent with external knowledge ties substituting for limited internal R&D capacity. Decomposing by partner type, the effect is largest for industry and clinical collaborations and smallest for academic ties, consistent with the former being closer to the regulatory and commercialisation process. Firms that bring AI devices to market display higher labour productivity, an effect robust for small firms and the full sample that holds under both sequential and joint maximum-likelihood estimation and accumulates across successive device introductions. Effects on profit margins are present but weaker and do not survive all specifications, a pattern consistent with competitive entry eroding pricing power as AI devices diffuse through the sector.
Problem

Research questions and friction points this paper is trying to address.

Artificial Intelligence
Firm Performance
Medical Device Industry
Innovation
Innovation

Methods, ideas, or system contributions that make the work stand out.

external AI research collaboration
AI device introduction
firm performance
medical technology sector
recursive model
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