Recombination of Knowledge Components and Knowledge Impact: Neighboring Components Versus Distant Components
研究了知识重组中搜索范围对知识影响的作用，发现重组邻近知识组件促进影响，而重组远距离组件则阻碍影响，基于专利数据验证了假设。
To date, existing studies have produced inconclusive empirical findings as to whether search scope impedes or benefits knowledge impact. To reconcile this controversy, we scrutinize the role of search scope and delve into the combination of knowledge components. Specifically, in this article, we propose that search scope connotes recombination of two types of novel components (i.e., recombining neighboring components or distant components). Drawing on the recombinant search and decomposability literature, we argue that recombining neighboring knowledge components is conducive to knowledge impact because these components provide absorbable variation and integration mechanisms, whereas recombining distant knowledge components impedes knowledge impact as the resultant outcome is difficult to understand and the value is not perceived. To empirically test these arguments, we draw on network function theory and develop a novel approach to build knowledge networks looking at the relatedness of knowledge components. Applying this method to data on patents granted from 1995 to 2009, we identify neighboring components and distant components as two related but different novel knowledge components. The results strongly support our hypotheses, even when controlling for the patent, inventor, as well as examiner level of covariates.