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Organizational Structure and Pricing: Evidence from a Large U.S. Airline

Author

Listed:
  • Ali Hortacsu

    (University of Chicago and NBER)

  • Olivia R. Natan

    (University of California, Berkeley)

  • Hayden Parsley

    (University of Texas, Austin)

  • Timothy Schwieg

    (University of Chicago, Booth)

  • Kevin R. Williams

    (Cowles Foundation, Yale University)

Abstract

We study how organizational boundaries affect pricing decisions using comprehensive data from a large U.S. airline. We document that the firm's advanced pricing algorithm, utilizing inputs from different organizational teams, is subject to multiple biases. To quantify the impacts of these biases, we estimate a structural demand model using sales and search data. We recover the demand curves the firm believes it faces using forecasting data. In counterfactuals, we show that correcting biases introduced by organizational teams individually have little impact on market outcomes, but coordinating organizational outcomes leads to higher prices/revenues and increased deadweight loss in the markets studied.

Suggested Citation

  • Ali Hortacsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," Cowles Foundation Discussion Papers 2312, Cowles Foundation for Research in Economics, Yale University.
    • Handle: RePEc:cwl:cwldpp:2312
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    References listed on IDEAS

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    Cited by:

    1. James D. Dana & Kevin R. Williams, 2022. "Intertemporal Price Discrimination in Sequential Quantity-Price Games," Marketing Science, INFORMS, vol. 41(5), pages 966-981, September.
    2. Victor Aguirregabiria & Francis Guiton, 2022. "Decentralized Decision-Making in Retail Chains: Evidence from Inventory Management," Working Papers tecipa-722, University of Toronto, Department of Economics.
    3. Michele Fioretti & Junnan He & Jorge Tamayo, 2024. "Prices and Concentration: A U-shape? Theory and Evidence from Renewables," Papers 2407.03504, arXiv.org.
    4. Ali Hortacsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Incorporating Search and Sales Information in Demand Estimation," Cowles Foundation Discussion Papers 2313, Cowles Foundation for Research in Economics, Yale University.
    5. Robert Evan Sanders, 2024. "Dynamic Pricing and Organic Waste Bans: A Study of Grocery Retailers’ Incentives to Reduce Food Waste," Marketing Science, INFORMS, vol. 43(2), pages 289-316, March.
    6. James D. Dana Jr. & Kevin R. Williams, 2018. "This paper develops an oligopoly model in which firms first choose capacity and then compete in prices in a series of advance-purchase markets. We show the existence of multiple sales opportunities cr," Cowles Foundation Discussion Papers 2136R4, Cowles Foundation for Research in Economics, Yale University, revised Nov 2021.

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    More about this item

    Keywords

    Pricing Frictions; Organizational Inertia; Dynamic Pricing; Revenue Management; Behavioral IO;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • L93 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Air Transportation

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