This book offers a comprehensive analysis of joint applications of patents from the EU, Japan and the USA, which directly signify collaborations between companies or inventors. It includes models that predict the probability of new connections.
This is the first book that comprehensively analyzes joint applications of patents from the European Union, Japan and the United States, which directly signify collaborations between companies or inventors, using the methodology of network science. Network science approaches enable us to predict structures of joint-application networks and to predict the impact of patents applied jointly. Regression analyses, which are broadly used in the field of economics, may be effective for determining what parameters are important for companies or inventors that are going to be connected, but they normally cannot rebuild the structures of networks from the model found through the analyses. Generative models in network science predict the probability of new connections for nodes. In line with this approach, this book also shows specific characteristics of joint-application networks of patents, such as link distance and layer interaction and it introduces models explaining the characteristics. This book discusses not only network structures but the impact of patents on networks, which is practically important. Again, a model found through regression analyses may show significant variables that make it possible to predict the impact of patents but such a model is generally not practically beneficial because the actual situations in which patents are created are so complex. However, if we restrict the situations for joint applications, that is, networks, we can get clear distributions of the impact of patents. This book describes how the impact of patents repeatedly applied by the same team decays and what the proper timing is to leave a decaying relationship.
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