Tracking innovation diffusion: AI analysis of large-scale patent data towards an agenda for further researchShow others and affiliations
2021 (English)In: Technological forecasting & social change, ISSN 0040-1625, E-ISSN 1873-5509, Vol. 165, article id 120524Article in journal (Refereed) Published
Abstract [en]
Recent advances in AI algorithms and computational power have led to opportunities for new methods and tools. Particularly when it comes to detecting the current status of inter-industry technologies, the new tools can be of great assistance. This is important because the research focus has been on how firms generate value through managing their business models. However, further attention needs to be given to the external technological opportunities that also contribute to value creation in firms. We applied unsupervised machine learning techniques, particularly DBSCAN, in an attempt to generate a macro-level technological map. Our results show that AI and machine learning tools can indeed be used for these purposes, and DBSCAN is a potential algorithm. Further research is needed to improve the maps and to use the generated data to study related phenomena including entrepreneurship.
Place, publisher, year, edition, pages
Elsevier, 2021. Vol. 165, article id 120524
Keywords [en]
AI, DBSCAN, Innovation diffusion, Tracking technology, Unsupervised machine learning, Business models, Computational power, Current status, Research focus, Technological opportunity, Value creation, Machine learning
National Category
Business Administration Computer and Information Sciences
Identifiers
URN: urn:nbn:se:sh:diva-43540DOI: 10.1016/j.techfore.2020.120524ISI: 000618756500015Scopus ID: 2-s2.0-85098940035OAI: oai:DiVA.org:sh-43540DiVA, id: diva2:1518105
2021-01-152021-01-152022-10-03Bibliographically approved