Identifying technology evolution pathways using topic variation detection based on patent data: A case study of 3D printing

Abstract Previous studies on identifying technology evolution pathways have ignored the point in time when an evolution pathway changes. To fill this gap in the literature, we use a novel approach based on text-mining to identify technology evolution pathways. First, the topic model was applied to discover technology topics, and topic variation through time was modeled. Second, critical junctures were detected based on topic variation to generate time segments. Finally, the main topics’ changes at different segments were analyzed to identify the pathway, and a visualization of the main topics’ trends were presented. To demonstrate the effectiveness of the text-mining approach, we examined 3D printing technologies using 34,090 patents from 1990 to 2017, and the database we used are updated weekly. We found that traditional technologies showed a declining trend, and their practical application technologies related to products is promising. The new approach can be applied to identify technology evolution pathways characterized by critical junctures. These critical junctures are helpful in understanding technological development more clearly, especially in identifying what and when technological changes occur.