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]
Innovation diffusion, AI, Unsupervised machine learning, DBSCAN, Tracking technology
National Category
Business Administration
Research subject
Entrepreneurship and Innovation
Identifiers
URN: urn:nbn:se:ltu:diva-82243DOI: 10.1016/j.techfore.2020.120524ISI: 000618756500015Scopus ID: 2-s2.0-85098940035OAI: oai:DiVA.org:ltu-82243DiVA, id: diva2:1515854
Note
Validerad;2021;Nivå 2;2021-01-11 (alebob);
Finansiär: Evald and Hilda Nissi Foundation
2021-01-112021-01-112021-03-11Bibliographically approved