The Path‐Dependent Nature of R&D Search: Implications for (and from) Competition
The Path‐Dependent Nature of R&D Search: Implications for (and from) Competition
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研发搜索的路径依赖性质：竞争的影响
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Stylianos Kavadias
中科院分区：
文献类型：
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作者：
Nektarios Oraiopoulos;Stylianos Kavadias
我们将研发形式化为跨越不同技术领域的技术改进的搜索过程。来自特定领域的技术改进利用公共知识库，因此它们共享技术内容。此外，不同的领域可能依赖于相似的科学原理，因此，一个领域的技术改进知识可能可转移到另一个领域。我们分析了当从过去的搜索努力中产生的知识传播到竞争对手公司时，这种技术相关性如何塑造研发搜索的方向。我们表明，公司最优地分散了他们的搜索努力，即使是在风险更大、期望更低的领域。这被放大为更高的竞争强度，即更高的交叉产品可替代性。我们的工作还表明，不同的领域学习来源可能对搜索方向产生相反的影响。推断探索领域潜力的能力越高，搜索就越聚类，而跨领域学习的能力就越多样化。最后，我们讨论了促使企业进行顺序研发搜索而不是平行竞争搜索的技术景观属性。
We formalize R&D as a search process for technology improvements across different technological domains. Technology improvements from a specific domain draw upon a common knowledge base, and as such they share technological content. Moreover, different domains may rely on similar scientific principles, and therefore, knowledge about the technology improvements by one domain might be transferable to another. We analyze how such a technological relatedness shapes the direction of R&D search when knowledge generated from past search efforts disseminates to rival firms. We show that firms optimally diversify their search efforts, even toward domains that are riskier and less promising on expectation. This is amplified for higher competition intensity, i.e., higher cross‐product substitutability. Our work also suggests that different sources of learning about the domains may have opposite effects on the direction of search. Higher ability to infer the potential of an explored domain prompts the clustering of searches, whereas the ability to learn across domains prompts diversification. Finally, we discuss the technological landscape properties that prompt firms to engage in a sequential R&D search, instead of a parallel competitive search.