IDEAS home Printed from https://ideas.repec.org/a/bla/randje/v55y2024i4p501-518.html

Steering via algorithmic recommendations

Author

Listed:
  • Nan Chen
  • Hsin‐Tien Tsai

Abstract

This article studies self‐preferencing in algorithmic recommendations on dominant platforms, focusing on Amazon's dual role as platform owner and retailer. We find that products sold by Amazon receive substantially more “Frequently Bought Together” recommendations across popularity deciles. To establish causality, we exploit within‐product variation generated by Amazon stockouts. We find that when Amazon is out of stock, identical products sold by third‐party sellers face an eight‐percentage‐point decrease in the probability of receiving a recommendation. The pattern can be explained by the economic incentives of steering but not explained by consumer preference. Furthermore, the steering lowers recommendation efficiency.

Suggested Citation

  • Nan Chen & Hsin‐Tien Tsai, 2024. "Steering via algorithmic recommendations," RAND Journal of Economics, RAND Corporation, vol. 55(4), pages 501-518, December.
    • Handle: RePEc:bla:randje:v:55:y:2024:i:4:p:501-518
    DOI: 10.1111/1756-2171.12481
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1756-2171.12481
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1756-2171.12481?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jay Pil Choi & Kyungmin Kim & Arijit Mukherjee, 2025. "“Sherlocking” and Platform Information Policy," Management Science, INFORMS, vol. 71(11), pages 9812-9830, November.
    2. Qu, Chuang & Liu, Hanzhen & Wang, Sai, 2025. "Is ranking position equal to pricing power?—Evidence from Chinese e-commerce platforms," International Review of Economics & Finance, Elsevier, vol. 98(C).
    3. Chang-Koo Chi & Jay Pil Choi & Jong-Hee Hahn & Seongkyun Kim, 2026. "Regulating Platform Bias: Self-Preferencing and Transaction Fees as Strategic Substitutes," CESifo Working Paper Series 12749, CESifo.
    4. Gambato, Jacopo & Sandrini, Luca, 2025. "Dance to my tune! Discovery mode and built-in recommendation bias," ZEW Discussion Papers 25-037, ZEW - Leibniz Centre for European Economic Research.
    5. Kaede Hanazawa, 2025. "Welfare Effects of Self-Preferencing by a Platform: Empirical Evidence from Airbnb," Papers 2503.04489, arXiv.org.
    6. Andres Hervas-Drane & Sandro Shelegia, 2025. "Retailer-Led Marketplaces," Management Science, INFORMS, vol. 71(11), pages 9650-9669, November.
    7. Tin Cheuk Leung & Shi Qi & Koleman Strumpf, 2025. "Dissecting Netflix's Self-Preferencing: Evidence from Viewer-Level Data," Working Papers 25-08, NET Institute.
    8. Markus Lill & Nastasia Gallitz & Lucas Stich & Martin Spann, 2026. "How Platform Endorsement Shapes Consumer Search and Choice in Online Retail," Rationality and Competition Discussion Paper Series 569, CRC TRR 190 Rationality and Competition.
    9. Clara, Jean & Jean-Flavien, Bussotti & Grazia, Cecere & Nessrine, Omrani & Paolo, Papotti, 2026. "Digital divide and artificial intelligence for health," Technovation, Elsevier, vol. 151(C).

    More about this item

    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:bla:randje:v:55:y:2024:i:4:p:501-518. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/randdus.html .

    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.