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What is the Market Value of Artificial Intelligence and Machine Learning?: The Role of Innovativeness and Collaboration for Performance
Hanken School of Economics, Vaasa, Finland.
Luleå University of Technology, Luleå, Sweden; University of Vaasa, School of Management, Vaasa, Finland.
Hanken School of Economics, Helsinki, Finland; University of St. Gallen, St. Gallen, Switzerland.
Luleå University of Technology, Luleå, Sweden.
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2022 (English)In: Technological forecasting & social change, ISSN 0040-1625, E-ISSN 1873-5509, Vol. 180, article id 121716Article in journal (Refereed) Published
Abstract [en]

As AI and ML technologies are increasingly incorporated into products, there is a need to understand the role of these incorporations in enhancing performance. This study uses new types of methodology related to textual data analysis to explore the question of whether there is a difference between market sentiments—and consequently marketing and business performance—when it comes to communicating either AI or ML. We test and confirm the hypothesis that AI rather than ML attracts more positive sentiments in the marketplace. Additionally, we find that AI is mostly used when the discussion centers on innovativeness, and that discussions concerning collaboration in these technologies attract more positive sentiments. We further contribute methodologically by leveraging textual data available online on the titles of web-page contents and the results of the Vader sentiment analysis to test our hypothesis. We conclude that, to enhance business performance, firms should communicate using AI-related vocabulary especially when the topic is innovativeness and collaboration.

Place, publisher, year, edition, pages
Elsevier, 2022. Vol. 180, article id 121716
Keywords [en]
AI, Collaboration, Innovativeness, Machine learning, Performance, Sentiment, Vader sentiment analysis, Commerce, Websites, Artificial intelligence learning, Business performance, Machine-learning, Market values, Sentiment analysis, Vade sentiment analyse
National Category
Business Administration Computer Sciences
Identifiers
URN: urn:nbn:se:sh:diva-49053DOI: 10.1016/j.techfore.2022.121716ISI: 000800612300011Scopus ID: 2-s2.0-85129530523OAI: oai:DiVA.org:sh-49053DiVA, id: diva2:1659125
Available from: 2022-05-19 Created: 2022-05-19 Last updated: 2022-10-03Bibliographically approved

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Oghazi, Pejvak

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  • ieee
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  • harvard-anglia-ruskin-university
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  • sodertorns-hogskola-harvard.csl
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