The Risk of De-Risking Innovation: Optimal R&D Strategies in Ambiguous Environments
研究了高度模糊条件下推动创新的框架，通过分析过去20年最具创新性的药物，发现大量小公司以更低总成本创造了更多突破，验证了分散化并行搜索在模糊环境中的优势，并指出试图通过缩小搜索范围来降低风险的策略可能过滤掉下一个突破。
This article develops a framework for driving innovation under highly ambiguous conditions. An analysis of the most novel medicines of the past 20 years shows that a very large group of small companies created more breakthroughs, at considerably less overall cost, than a much smaller group of very large companies. This article’s findings present the first large-scale empirical validation of the theoretical literature predicting the superiority of decentralized parallel searches in ambiguous environments. Accordingly, companies that attempt to “de-risk” the innovation portfolio by narrowing their search efforts to minimize failures run the risk of filtering out the next breakthrough.