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What is the Market Value of Artificial Intelligence and Machine Learning? The Role of Innovativeness and Collaboration for Performance

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  • Fredström, Ashkan
  • Parida, Vinit
  • Wincent, Joakim
  • Sjödin, David
  • Oghazi, Pejvak

Abstract

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.

Suggested Citation

  • Fredström, Ashkan & Parida, Vinit & Wincent, Joakim & Sjödin, David & Oghazi, Pejvak, 2022. "What is the Market Value of Artificial Intelligence and Machine Learning? The Role of Innovativeness and Collaboration for Performance," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    • Handle: RePEc:eee:tefoso:v:180:y:2022:i:c:s0040162522002426
    DOI: 10.1016/j.techfore.2022.121716
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    1. Shen, Lei & Shi, Qingyue & Panda, Debadrita & Parida, Vinit, 2026. "Digital technology diffusion through supply chain orchestration," Technological Forecasting and Social Change, Elsevier, vol. 225(C).
    2. Gao, Yang & Liu, Siqiang & Yang, Lu, 2025. "Artificial intelligence and innovation capability: A dynamic capabilities perspective," International Review of Economics & Finance, Elsevier, vol. 98(C).
    3. Yogesh K. Dwivedi & A. Sharma & Nripendra P. Rana & M. Giannakis & P. Goel & Vincent Dutot, 2023. "Evolution of Artificial Intelligence Research in Technological Forecasting and Social Change: Research Topics, Trends, and Future Directions," Post-Print hal-04292607, HAL.
    4. Chao Xu & Sung-Eui Cho, 2025. "Factors Affecting Human–AI Collaboration Performances in Financial Sector: Sustainable Service Development Perspective," Sustainability, MDPI, vol. 17(10), pages 1-28, May.

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