Hard to get? Tracking Knowledge Heritage From Invention to Product Market Innovation Using NLP
Sheryl Winston Smith · Academy of Management Proceedings · 2019
Patents and patent citations are a window into the innovation process. Yet even established firms have difficulty commercializing inventions. A conundrum for scholars is: does the inventive activity captured in patents and patent citations translate into innovation in the product market? In other words, how reliably can we understand the link between patents and introduction of novel products to market? Thus, unpacking the link between knowledge and innovation is crucial for innovation, entrepreneurship, and strategy scholars. This paper brings to the innovation literature an important methodological approach from computer science: application of natural language processing and the vector space model in information retrieval to the study of innovation. Specifically, this paper details a novel methodology to algorithmically compare the similarity of patent texts to the description of innovations in two distinct contexts: 1) novel products brought to market by corporate venture capital investors in the medical device industry , and 2) IPO prospectus of startups in the communications equipment industry.