Neighboring Knowledge Recombination: Knowledge Relationship Intensity, Neighboring Knowledge Concentration, and Knowledge Impact

Abstract

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.