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Artificial intelligence adoption in a monopoly market

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  • Joshua S. Gans

Abstract

The adoption of artificial intelligence (AI) prediction of demand by a monopolist firm is examined. It is shown that, in the absence of AI prediction, firms face complex trade‐offs in setting price and quantity ahead of demand that impact on the returns of AI adoption. Different industrial environments with differing flexibility of prices and/or quantity ex post also impact on AI returns as does the time horizon of AI prediction. While AI has positive benefits for firms in terms of profitability, its impact on average price and quantity, as well as consumer welfare, is more nuanced and critically dependent on environmental characteristics.

Suggested Citation

  • Joshua S. Gans, 2023. "Artificial intelligence adoption in a monopoly market," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(2), pages 1098-1106, March.
  • Handle: RePEc:wly:mgtdec:v:44:y:2023:i:2:p:1098-1106
    DOI: 10.1002/mde.3734
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    References listed on IDEAS

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    1. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation, and Work," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 197-236, National Bureau of Economic Research, Inc.
    2. Kevin A. Bryan & Heidi L. Williams, 2021. "Innovation: Market Failures and Public Policies," NBER Working Papers 29173, National Bureau of Economic Research, Inc.
    3. Ajay K. Agrawal & Joshua S. Gans & Avi Goldfarb, 2021. "AI Adoption and System-Wide Change," NBER Working Papers 28811, National Bureau of Economic Research, Inc.
    4. Emilio Calvano & Giacomo Calzolari & Vincenzo Denicolò & Sergio Pastorello, 2020. "Artificial Intelligence, Algorithmic Pricing, and Collusion," American Economic Review, American Economic Association, vol. 110(10), pages 3267-3297, October.
    5. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    6. Sabrina Schneider & Michael Leyer, 2019. "Me or information technology? Adoption of artificial intelligence in the delegation of personal strategic decisions," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 40(3), pages 223-231, April.
    7. Agrawal, Ajay & Gans, Joshua S. & Goldfarb, Avi, 2019. "Exploring the impact of artificial Intelligence: Prediction versus judgment," Information Economics and Policy, Elsevier, vol. 47(C), pages 1-6.
    8. Edwin S. Mills, 1959. "Uncertainty and Price Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 73(1), pages 116-130.
    9. repec:bla:scandj:v:90:y:1988:i:3:p:275-89 is not listed on IDEAS
    10. Joshua S. Gans, 2022. "AI Adoption in a Competitive Market," NBER Working Papers 29996, National Bureau of Economic Research, Inc.
    11. Agrawal, Ajay & Gans, Joshua & Goldfarb, Avi (ed.), 2019. "The Economics of Artificial Intelligence," National Bureau of Economic Research Books, University of Chicago Press, number 9780226613338.
    12. Pınar Keskinocak & Kasarin Chivatxaranukul & Paul M. Griffin, 2008. "Strategic inventory in capacitated supply chain procurement," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 23-36.
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    1. Agrawal, Ajay & Gans, Joshua S. & Goldfarb, Avi, 2024. "Prediction machines, insurance, and protection: An alternative perspective on AI’s role in production," Journal of the Japanese and International Economies, Elsevier, vol. 72(C).

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