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Contracting, Pricing, and Data Collection Under the AI Flywheel Effect

Author

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  • Huseyin Gurkan

    (European School of Management and Technology Berlin, 10178 Berlin, Germany)

  • Francis de Véricourt

    (European School of Management and Technology Berlin, 10178 Berlin, Germany)

Abstract

This paper explores how firms that lack expertise in machine learning (ML) can leverage the so-called AI Flywheel effect. This effect designates a virtuous cycle by which as an ML product is adopted and new user data are fed back to the algorithm, the product improves, enabling further adoptions. However, managing this feedback loop is difficult, especially when the algorithm is contracted out. Indeed, the additional data that the AI Flywheel effect generates may change the provider’s incentives to improve the algorithm over time. We formalize this problem in a simple two-period moral hazard framework that captures the main dynamics among ML, data acquisition, pricing, and contracting. We find that the firm’s decisions crucially depend on how the amount of data on which the machine is trained interacts with the provider’s effort. If this effort has a more (less) significant impact on accuracy for larger volumes of data, the firm underprices (overprices) the product. Interestingly, these distortions sometimes improve social welfare, which accounts for the customer surplus and profits of both the firm and provider. Further, the interaction between incentive issues and the positive externalities of the AI Flywheel effect has important implications for the firm’s data collection strategy. In particular, the firm can boost its profit by increasing the product’s capacity to acquire usage data only up to a certain level. If the product collects too much data per user, the firm’s profit may actually decrease (i.e., more data are not necessarily better).

Suggested Citation

  • Huseyin Gurkan & Francis de Véricourt, 2022. "Contracting, Pricing, and Data Collection Under the AI Flywheel Effect," Management Science, INFORMS, vol. 68(12), pages 8791-8808, December.
  • Handle: RePEc:inm:ormnsc:v:68:y:2022:i:12:p:8791-8808
    DOI: 10.1287/mnsc.2022.4333
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    References listed on IDEAS

    as
    1. Francis de Véricourt & Denis Gromb, 2019. "Financing Capacity with Stealing and Shirking," Management Science, INFORMS, vol. 65(11), pages 5128-5141, November.
    2. Gabszewicz, Jean J. & Garcia, Filomena, 2008. "A note on expanding networks and monopoly pricing," Economics Letters, Elsevier, vol. 98(1), pages 9-15, January.
    3. Arthur Campbell, 2013. "Word-of-Mouth Communication and Percolation in Social Networks," American Economic Review, American Economic Association, vol. 103(6), pages 2466-2498, October.
    4. Oz Shy, 2011. "A Short Survey of Network Economics," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 38(2), pages 119-149, March.
    5. Alles, M & Datar, SM & Lambert, RA, 1995. "Moral hazard and management control in just-in-time settings," Journal of Accounting Research, Wiley Blackwell, vol. 33, pages 177-204.
    6. Loertscher, Simon & Marx, Leslie M., 2020. "Digital monopolies: Privacy protection or price regulation?," International Journal of Industrial Organization, Elsevier, vol. 71(C).
    7. Cabral, Luis M. B. & Salant, David J. & Woroch, Glenn A., 1999. "Monopoly pricing with network externalities," International Journal of Industrial Organization, Elsevier, vol. 17(2), pages 199-214, February.
    8. Heese, H. Sebastian & Swaminathan, Jayashankar M., 2010. "Inventory and sales effort management under unobservable lost sales," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1263-1268, December.
    9. Sameer Mehta & Milind Dawande & Ganesh Janakiraman & Vijay Mookerjee, 2021. "How to Sell a Data Set? Pricing Policies for Data Monetization," Information Systems Research, INFORMS, vol. 32(4), pages 1281-1297, December.
    10. Schmitz, Patrick W., 2013. "Job design with conflicting tasks reconsidered," European Economic Review, Elsevier, vol. 57(C), pages 108-117.
    11. Robert Swinney & Gérard P. Cachon & Serguei Netessine, 2011. "Capacity Investment Timing by Start-ups and Established Firms in New Markets," Management Science, INFORMS, vol. 57(4), pages 763-777, April.
    12. Gromb, Denis & Martimort, David, 2007. "Collusion and the organization of delegated expertise," Journal of Economic Theory, Elsevier, vol. 137(1), pages 271-299, November.
    13. Patrick W. Schmitz, 2005. "Allocating Control in Agency Problems with Limited Liability and Sequential Hidden Actions," RAND Journal of Economics, The RAND Corporation, vol. 36(2), pages 318-336, Summer.
    14. Vidyanand Choudhary & Anindya Ghose & Tridas Mukhopadhyay & Uday Rajan, 2005. "Personalized Pricing and Quality Differentiation," Management Science, INFORMS, vol. 51(7), pages 1120-1130, July.
    15. Bensaid, Bernard & Lesne, Jean-Philippe, 1996. "Dynamic monopoly pricing with network externalities," International Journal of Industrial Organization, Elsevier, vol. 14(6), pages 837-855, October.
    16. Tinglong Dai & Kinshuk Jerath, 2019. "Salesforce Contracting Under Uncertain Demand and Supply: Double Moral Hazard and Optimality of Smooth Contracts," Marketing Science, INFORMS, vol. 38(5), pages 852-870, September.
    17. Edward G. Anderson Jr. & Geoffrey G. Parker, 2013. "Integration and Cospecialization of Emerging Complementary Technologies by Startups," Production and Operations Management, Production and Operations Management Society, vol. 22(6), pages 1356-1373, November.
    18. Michael L. Katz & Carl Shapiro, 1994. "Systems Competition and Network Effects," Journal of Economic Perspectives, American Economic Association, vol. 8(2), pages 93-115, Spring.
    19. Tinglong Dai & Kinshuk Jerath, 2013. "Salesforce Compensation with Inventory Considerations," Management Science, INFORMS, vol. 59(11), pages 2490-2501, November.
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