Item Type | Conference or Workshop Item (Paper) |
Abstract | This study examines how firms in the autonomous driving industry that pursue artificial intelligence-based innovations attempt to appropriate returns from these innovations. It intends to contribute to the literature on value appropriation from innovation by investigating the extent to which firms can and do keep the key components of AI systems (data set, training approach, and model) private versus publishing them. Using a qualitative research design, we establish that there are regulatory, technical, and enforcement aspects to the components that prompt firms to either protect or publish. |
Authors | Häfner, Naomi; Gassmann, Oliver & Borth, Damian |
Language | English |
Subjects | business studies |
HSG Classification | contribution to scientific community |
HSG Profile Area | SoM - Business Innovation |
Date | 27 March 2020 |
Publisher | SMS Strategic Management Society |
Place of Publication | Chicago, IL |
Number of Pages | 7 |
Title of Book | The Institutional and Regulatory Levers of Innovation and Venture Formation |
Event Title | Strategic Management Society Special Conference |
Event Location | Berkeley, CA |
Event Dates | March 25-27, 2020 |
Official URL | https://www.strategicmanagement.net/berkeley/overv... |
Depositing User | Prof. Dr. Naomi Häfner |
Date Deposited | 09 Oct 2020 09:57 |
Last Modified | 09 Oct 2020 09:57 |
URI: | https://www.alexandria.unisg.ch/publications/261181 |
DownloadFull text not available from this repository.CitationHäfner, Naomi; Gassmann, Oliver & Borth, Damian: Intellectual property protection in the age of self-learning systems: Appropriability issues in artificial intelligence. 2020. - Strategic Management Society Special Conference. - Berkeley, CA. Statisticshttps://www.alexandria.unisg.ch/id/eprint/261181
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