IDEAS home Printed from https://ideas.repec.org/p/bon/boncrc/crctr224_2023_411.html
   My bibliography  Save this paper

Value for Money and Selection: How Pricing Affects Airbnb Ratings

Author

Listed:
  • Christoph Carnehl
  • Maximilian Schaefer
  • Andre Stenzel
  • Kevin Ducbao Tran

Abstract

We investigate the impact of prices on ratings using Airbnb data. We theoretically illustrate two opposing channels: higher prices reduce the value for money, worsening ratings, but they increase the taste-based valuation of the average traveler, improving ratings. Results from panel regressions and a regression discontinuity design suggest a dominant value-for-money effect. In line with our model, hosts strategically complement lower prices with higher effort more when ratings are relatively low. Finally, we provide evidence that, upon entry, strategic hosts exploit the dominant value-for-money effect. The median entry discount of seven percent improves medium-run monthly revenues by three percent.

Suggested Citation

  • Christoph Carnehl & Maximilian Schaefer & Andre Stenzel & Kevin Ducbao Tran, 2023. "Value for Money and Selection: How Pricing Affects Airbnb Ratings," CRC TR 224 Discussion Paper Series crctr224_2023_411, University of Bonn and University of Mannheim, Germany.
    • Handle: RePEc:bon:boncrc:crctr224_2023_411
    as

    Download full text from publisher

    File URL: https://www.crctr224.de/research/discussion-papers/archive/dp411
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Dina Mayzlin & Yaniv Dover & Judith Chevalier, 2014. "Promotional Reviews: An Empirical Investigation of Online Review Manipulation," American Economic Review, American Economic Association, vol. 104(8), pages 2421-2455, August.
    2. Kilian Huber & Volker Lindenthal & Fabian Waldinger, 2021. "Discrimination, Managers, and Firm Performance: Evidence from “Aryanizations” in Nazi Germany," Journal of Political Economy, University of Chicago Press, vol. 129(9), pages 2455-2503.
    3. Andrey Fradkin & Elena Grewal & David Holtz, 2021. "Reciprocity and Unveiling in Two-Sided Reputation Systems: Evidence from an Experiment on Airbnb," Marketing Science, INFORMS, vol. 40(6), pages 1013-1029, November.
    4. Zemin (Zachary) Zhong, 2022. "Chasing Diamonds and Crowns: Consumer Limited Attention and Seller Response," Management Science, INFORMS, vol. 68(6), pages 4380-4397, June.
    5. Luís Cabral & Lingfang (Ivy) Li, 2015. "A Dollar for Your Thoughts: Feedback-Conditional Rebates on eBay," Management Science, INFORMS, vol. 61(9), pages 2052-2063, September.
    6. Sherry He & Brett Hollenbeck & Davide Proserpio, 2022. "The Market for Fake Reviews," Marketing Science, INFORMS, vol. 41(5), pages 896-921, September.
    7. Michael Luca, 2011. "Reviews, Reputation, and Revenue: The Case of Yelp.com," Harvard Business School Working Papers 12-016, Harvard Business School, revised Mar 2016.
    8. Davide Proserpio & Georgios Zervas, 2017. "Online Reputation Management: Estimating the Impact of Management Responses on Consumer Reviews," Marketing Science, INFORMS, vol. 36(5), pages 645-665, September.
    9. Michael Luca & Oren Reshef, 2021. "The Effect of Price on Firm Reputation," Management Science, INFORMS, vol. 67(7), pages 4408-4419, July.
    10. Jeffrey A. Livingston, 2005. "How Valuable Is a Good Reputation? A Sample Selection Model of Internet Auctions," The Review of Economics and Statistics, MIT Press, vol. 87(3), pages 453-465, August.
    11. Kristina Shampanier & Nina Mazar & Dan Ariely, 2007. "Zero as a Special Price: The True Value of Free Products," Marketing Science, INFORMS, vol. 26(6), pages 742-757, 11-12.
    12. Steven Tadelis, 2016. "Reputation and Feedback Systems in Online Platform Markets," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 321-340, October.
    13. Michael Luca & Georgios Zervas, 2016. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud," Management Science, INFORMS, vol. 62(12), pages 3412-3427, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lingfang (Ivy) Li & Steven Tadelis & Xiaolan Zhou, 2020. "Buying reputation as a signal of quality: Evidence from an online marketplace," RAND Journal of Economics, RAND Corporation, vol. 51(4), pages 965-988, December.
    2. Gesche, Tobias, 2018. "Reference Price Shifts and Customer Antagonism: Evidence from Reviews for Online Auctions," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181650, Verein für Socialpolitik / German Economic Association.
    3. Michael Luca & Oren Reshef, 2021. "The Effect of Price on Firm Reputation," Management Science, INFORMS, vol. 67(7), pages 4408-4419, July.
    4. Michael Luca & Oren Reshef, 2020. "The Effect of Price on Firm Reputation," NBER Working Papers 27405, National Bureau of Economic Research, Inc.
    5. Erfan Rezvani & Christian Rojas, 2022. "Firm responsiveness to consumers' reviews: The effect on online reputation," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 31(4), pages 898-922, November.
    6. Apostolos Filippas & John J. Horton & Joseph M. Golden, 2022. "Reputation Inflation," Marketing Science, INFORMS, vol. 41(4), pages 733-745, July.
    7. Brett Hollenbeck & Sridhar Moorthy & Davide Proserpio, 2019. "Advertising Strategy in the Presence of Reviews: An Empirical Analysis," Marketing Science, INFORMS, vol. 38(5), pages 793-811, September.
    8. Jürgen Neumann, 2021. "When Biased Ratings Benefit the Consumer - An Economic Analysis of Online Ratings in Markets with Variety-Seeking Consumers," Working Papers Dissertations 77, Paderborn University, Faculty of Business Administration and Economics.
    9. Paul Belleflamme & Martin Peitz, 2018. "Inside the Engine Room of Digital Platforms: Reviews, Ratings, and Recommendations," Working Papers halshs-01714549, HAL.
    10. Georgios Zervas & Davide Proserpio & John W. Byers, 2021. "A first look at online reputation on Airbnb, where every stay is above average," Marketing Letters, Springer, vol. 32(1), pages 1-16, March.
    11. Tommaso Bondi, 2019. "Alone, Together. Product Discovery Through Consumer Ratings," Working Papers 19-09, NET Institute.
    12. Guo, Qiaozhen & Chen, Ying-Ju & Huang, Wei, 2022. "Dynamic pricing of new experience products with dual-channel social learning and online review manipulations," Omega, Elsevier, vol. 109(C).
    13. Greiff, Matthias & Paetzel, Fabian, 2020. "Information about average evaluations spurs cooperation: An experiment on noisy reputation systems," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 334-356.
    14. Andrey Fradkin & David Holtz, 2023. "Do Incentives to Review Help the Market? Evidence from a Field Experiment on Airbnb," Marketing Science, INFORMS, vol. 42(5), pages 853-865, September.
    15. Gary Bolton & Kevin Breuer & Ben Greiner & Axel Ockenfels, 2023. "Fixing feedback revision rules in online markets," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 32(2), pages 247-256, April.
    16. Dominik Gutt & Jürgen Neumann & Steffen Zimmermann & Dennis Kundisch & Jianqing Chen, 2018. "Design of Review Systems - A Strategic Instrument to shape Online Review Behavior and Economic Outcomes," Working Papers Dissertations 42, Paderborn University, Faculty of Business Administration and Economics.
    17. Surachartkumtonkun, Jiraporn (Nui) & Grace, Debra & Ross, Mitchell, 2021. "Unfair customer reviews: Third-party perceptions and managerial responses," Journal of Business Research, Elsevier, vol. 132(C), pages 631-640.
    18. Ishita Chakraborty & Minkyung Kim & K. Sudhir, 2019. "Attribute Sentiment Scoring With Online Text Reviews : Accounting for Language Structure and Attribute Self-Selection," Cowles Foundation Discussion Papers 2176R, Cowles Foundation for Research in Economics, Yale University, revised Sep 2020.
    19. Young Joon Park & Jaewoo Joo & Charin Polpanumas & Yeujun Yoon, 2021. "“Worse Than What I Read?” The External Effect of Review Ratings on the Online Review Generation Process: An Empirical Analysis of Multiple Product Categories Using Amazon.com Review Data," Sustainability, MDPI, vol. 13(19), pages 1-22, September.
    20. Nikhil Garg & Ramesh Johari, 2021. "Designing Informative Rating Systems: Evidence from an Online Labor Market," Manufacturing & Service Operations Management, INFORMS, vol. 23(3), pages 589-605, May.

    More about this item

    Keywords

    Rating Systems; Dynamic Pricing; Asymmetric Information;
    All these keywords.

    JEL classification:

    • D18 - Microeconomics - - Household Behavior - - - Consumer Protection
    • D25 - Microeconomics - - Production and Organizations - - - Intertemporal Firm Choice: Investment, Capacity, and Financing
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bon:boncrc:crctr224_2023_411. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CRC Office (email available below). General contact details of provider: https://www.crctr224.de .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.