Long Jump Learning: Absorbing Distant Knowledge via Familiar Components

跳跃 知识管理 计算机科学 认知科学 认知心理学 心理学 物理 量子力学
作者
Christian Mealey,Balaji R. Koka,Robert E. Hoskisson
出处
期刊:Organization Science [Institute for Operations Research and the Management Sciences]
卷期号:36 (4): 1598-1624 被引量:1
标识
DOI:10.1287/orsc.2019.13171
摘要

How do firms overcome the challenge of absorbing distant knowledge? Scholars argue that organizations need knowledge that is distant from their existing knowledge base to create novel innovative output, whereas others argue, in contrast, that organizations need knowledge to be similar to the firm’s knowledge base in order to absorb it. We argue that organizations can improve their ability to identify and comprehend knowledge from a distant knowledge category through learning associations made by a category link—a familiar tangible component previously used by somebody else in the distant knowledge category. We test our arguments using a sample of patents in which the material graphene is used as a component across diverse patent classes (i.e., knowledge categories). We find that increasing experience with category-linking graphene enables an organization to patent in increasingly distant graphene-linked patent classes and also increases the number of patents in such classes. We also find that the extent to which category-linking graphene is prominent in a distant knowledge category enhances the effect of graphene experience on a firm’s ability to absorb knowledge from the distant knowledge category. We, thus, present a novel internal mechanism by which an organization can absorb distant knowledge.
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