We propose a new method to characterize firms' inventive activities via topological data analysis (TDA) that represents high-dimensional data in a shape graph. Applying this method to 333 major firms' patents in 1976-2005 reveals substantial heterogeneity: some firms remain undifferentiated; others develop unique portfolios. Firms with unique trajectories, which we define graph-theoretically as "flares" in the Mapper graph, perform better. This association is statistically and economically significant, and continues to hold after we control for portfolio size and firm survivorship. Comparison with existing techniques suggests the method's usefulness for data visualization and exploratory empirical research more generally.
翻译:我们提出一种新的方法,通过地形数据分析(TDA)来描述公司的创造性活动,该方法在形状图中代表了高维数据。在1976-2005年将这种方法应用于333个大公司的专利,揭示了巨大的异质性:一些公司仍然没有差别;另一些公司则开发独特的投资组合。在地图图中,具有独特轨迹的公司(我们在地图图中将其图形-理论定义为“Flares ” ) 表现得更好。这一联系在统计和经济方面意义重大,并且在我们控制投资组合规模和公司生存能力之后继续维持下去。与现有技术的比较表明,该方法对于数据可视化和更广义的探索性实验性研究是有用的。