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Menu Pricing and Learning

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  • Alessandro Bonatti

Abstract

We analyze the design of dynamic menus to sell experience goods. The quality of the product is initially unknown, and the total quantity sold in each period determines the amount of information in the market. We characterize the optimum menu as a function of consumers' beliefs, and the dynamic adjustments resulting from the diffusion of information. The firm faces a dynamic trade-off between gains from trade, information production, and information rents. It initially charges lower prices, sacrificing short-term revenue to increase sales. As more information is revealed, prices increase, and low-valuation buyers are excluded, even when the product's quality is high. (JEL D42, D82, D83, L12)

Suggested Citation

  • Alessandro Bonatti, 2011. "Menu Pricing and Learning," American Economic Journal: Microeconomics, American Economic Association, vol. 3(3), pages 124-163, August.
    • Handle: RePEc:aea:aejmic:v:3:y:2011:i:3:p:124-63
    Note: DOI: 10.1257/mic.3.3.124
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    References listed on IDEAS

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    Cited by:

    1. Fei Li & Xi Weng, 2017. "Efficient Learning And Job Turnover In The Labor Market," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 58(3), pages 727-750, August.
    2. Martin Peitz & Sven Rady & Piers Trepper, 2017. "Experimentation in Two-Sided Markets," Journal of the European Economic Association, European Economic Association, vol. 15(1), pages 128-172.
    3. Eeckhout, Jan & Weng, Xi, 2015. "Common value experimentation," Journal of Economic Theory, Elsevier, vol. 160(C), pages 317-339.
    4. Keller, Godfrey & Rady, Sven, 2020. "Undiscounted bandit games," Games and Economic Behavior, Elsevier, vol. 124(C), pages 43-61.
    5. Qianjun Lyu, 2022. "Optimal Refund Mechanism," ECONtribute Discussion Papers Series 214, University of Bonn and University of Cologne, Germany.
    6. Benjamin R. Handel & Kanishka Misra, 2015. "Robust New Product Pricing," Marketing Science, INFORMS, vol. 34(6), pages 864-881, November.
    7. Keller, Godfrey & Rady, Sven, 2015. "Breakdowns," Theoretical Economics, Econometric Society, vol. 10(1), January.
    8. Mihaela Schaar & Simpson Zhang, 2015. "A dynamic model of certification and reputation," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 58(3), pages 509-541, April.
    9. Weng, Xi, 2015. "Dynamic pricing in the presence of individual learning," Journal of Economic Theory, Elsevier, vol. 155(C), pages 262-299.
    10. Monire Jalili & Michael S. Pangburn, 2020. "Pricing Joint Sales and Rentals: When are Purchase Conversion Discounts Optimal?," Production and Operations Management, Production and Operations Management Society, vol. 29(12), pages 2679-2695, December.
    11. Kanishka Misra & Eric M. Schwartz & Jacob Abernethy, 2019. "Dynamic Online Pricing with Incomplete Information Using Multiarmed Bandit Experiments," Marketing Science, INFORMS, vol. 38(2), pages 226-252, March.
    12. Weber, Thomas A. & Nguyen, Viet Anh, 2018. "A linear-quadratic Gaussian approach to dynamic information acquisition," European Journal of Operational Research, Elsevier, vol. 270(1), pages 260-281.

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    More about this item

    JEL classification:

    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L12 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Monopoly; Monopolization Strategies

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