Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Artificial intelligence and innovation management: A review, framework, and research agenda
University of St. Gallen, St. Gallen, Switzerland.
University of St. Gallen, St. Gallen, Switzerland. Hanken, School of Economics, Entrepreneurship and Management, Helsinki, Finland.ORCID iD: 0000-0002-8770-8874
Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering. University of South-Eastern Norway, Entrepreneurship and Innovation/USN Business School, Vestfold, Norway. University of Vaasa, School of Management, Vaasa, Finland .ORCID iD: 0000-0003-3255-414X
University of St. Gallen, St. Gallen, Switzerland.
2021 (English)In: Technological forecasting & social change, ISSN 0040-1625, E-ISSN 1873-5509, Vol. 162, article id 120392Article in journal (Refereed) Published
Abstract [en]

Artificial Intelligence (AI) reshapes companies and how innovation management is organized. Consistent with rapid technological development and the replacement of human organization, AI may indeed compel management to rethink a company’s entire innovation process. In response, we review and explore the implications for future innovation management. Using ideas from the Carnegie School and the behavioral theory of the firm, we review the implications for innovation management of AI technologies and machine learning-based AI systems. We outline a framework showing the extent to which AI can replace humans and explain what is important to consider in making the transformation to the digital organization of innovation. We conclude our study by exploring directions for future research. © 2020 The Author(s)

Place, publisher, year, edition, pages
Elsevier, 2021. Vol. 162, article id 120392
Keywords [en]
Technological forecasting, AI systems, AI Technologies, Behavioral theory of the firms, Implications for futures, Innovation management, Innovation process, Research agenda, Technological development, Artificial intelligence, artificial intelligence, information processing, innovation, literature review, machine learning, research
National Category
Business Administration
Research subject
Entrepreneurship and Innovation
Identifiers
URN: urn:nbn:se:ltu:diva-81529DOI: 10.1016/j.techfore.2020.120392ISI: 000601162500015Scopus ID: 2-s2.0-85092748091OAI: oai:DiVA.org:ltu-81529DiVA, id: diva2:1503377
Note

Validerad;2020;Nivå 2;2020-11-24 (johcin)

Available from: 2020-11-24 Created: 2020-11-24 Last updated: 2021-01-14Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Wincent, JoakimParida, Vinit

Search in DiVA

By author/editor
Wincent, JoakimParida, Vinit
By organisation
Business Administration and Industrial Engineering
In the same journal
Technological forecasting & social change
Business Administration

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 508 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf