Neighboring Knowledge Recombination: Knowledge Relationship Intensity, Neighboring Knowledge Concentration, and Knowledge Impact
研究了知识关系强度和邻近知识集中度对知识影响的倒U形作用，以及技术不确定性如何强化这种关系，基于美国专利数据构建知识网络进行分析。
Recent research on recombinant search has paid close attention to the search for and recombination of useful knowledge pieces. However, the question of where to search and how to allocate inventive efforts remains underdeveloped. This article identifies knowledge relationship intensity and neighboring knowledge concentration as critical factors and highlights the contingent role of technological uncertainty. Drawing on a novel network construction method, we built knowledge networks of U.S. utility patents granted from 1995 to 2009. Then we developed an elaborated measure of knowledge relationship intensity and neighboring knowledge concentration. Our findings suggest that knowledge relationship intensity and neighboring knowledge concentration have a curvilinear (inverted U-shaped) relationship with knowledge impact. Furthermore, technological uncertainty accentuates both the effects of knowledge relationship intensity and neighboring knowledge concentration on knowledge impact in such a way that makes curvilinear relationships move upward. This article provides important theoretical and practical implications.