IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/25917.html
   My bibliography  Save this paper

Steering in Online Markets: The Role of Platform Incentives and Credibility

Author

Listed:
  • Moshe A. Barach
  • Joseph M. Golden
  • John J. Horton

Abstract

Platform marketplaces can potentially steer buyers to certain sellers by recommending or guaranteeing those sellers. Money-back guarantees—which create a direct financial stake for the platform in seller performance—might be particularly effective at steering, as they align buyer and platform interests in creating a good match. We report the results of an experiment in which a platform marketplace—an online labor market—guaranteed select sellers for treated buyers. The presence of a guarantee strongly steered buyers to these guaranteed sellers, but offering guarantees did not increase sales overall, suggesting financial risk was not determinative for the marginal buyer. This preference for guaranteed sellers was not the result of their lower financial risk, but rather because buyers viewed the platform’s decision to guarantee as informative about relative seller quality. Indeed, a follow-up experiment showed that simply recommending the sellers that the platform would have guaranteed was equally effective at steering buyers.

Suggested Citation

  • Moshe A. Barach & Joseph M. Golden & John J. Horton, 2019. "Steering in Online Markets: The Role of Platform Incentives and Credibility," NBER Working Papers 25917, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:25917
    Note: LS PR
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w25917.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Bruce McWilliams, 2012. "Money-Back Guarantees: Helping the Low-Quality Retailer," Management Science, INFORMS, vol. 58(8), pages 1521-1524, August.
    2. Jennifer L. Doleac & Luke C.D. Stein, 2013. "The Visible Hand: Race and Online Market Outcomes," Economic Journal, Royal Economic Society, vol. 123(11), pages 469-492, November.
    3. Chris Nosko & Steven Tadelis, 2015. "The Limits of Reputation in Platform Markets: An Empirical Analysis and Field Experiment," NBER Working Papers 20830, National Bureau of Economic Research, Inc.
    4. Ajay K. Agrawal & Nicola Lacetera & Elizabeth Lyons, 2013. "Does Information Help or Hinder Job Applicants from Less Developed Countries in Online Markets?," NBER Working Papers 18720, National Bureau of Economic Research, Inc.
    5. Basil Halperin & Benjamin Ho & John List & Ian Muir, 2018. "Toward an understanding of the economics of apologies: evidence from a large-scale natural field experiment," Natural Field Experiments 00644, The Field Experiments Website.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Casner, Ben, 2020. "Seller curation in platforms," International Journal of Industrial Organization, Elsevier, vol. 72(C).
    2. Moshe A. Barach & Aseem Kaul & Ming D. Leung & Sibo Lu, 2019. "Strategic Redundancy in the Use of Big Data: Evidence from a Two-Sided Labor Market," Strategy Science, INFORMS, vol. 4(4), pages 298-322, December.

    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. Moshe A. Barach & Joseph M. Golden & John J. Horton, 2020. "Steering in Online Markets: The Role of Platform Incentives and Credibility," Management Science, INFORMS, vol. 66(9), pages 4047-4070, September.
    2. Tjaden, Jasper & Schwemmer, Carsten & Khadjavi, Menusch, 2018. "Ride with Me - Ethnic Discrimination, Social Markets and the Sharing Economy," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181507, Verein für Socialpolitik / German Economic Association.
    3. Alan Benson & Aaron Sojourner & Akhmed Umyarov, 2020. "Can Reputation Discipline the Gig Economy? Experimental Evidence from an Online Labor Market," Management Science, INFORMS, vol. 66(5), pages 1802-1825, May.
    4. Daniel W. Elfenbein & Raymond Fisman & Brian McManus, 2019. "The Impact of Socioeconomic and Cultural Differences on Online Trade," NBER Working Papers 26197, National Bureau of Economic Research, Inc.
    5. Mujcic, Redzo & Frijters, Paul, 2013. "Still Not Allowed on the Bus: It Matters If You're Black or White!," IZA Discussion Papers 7300, Institute of Labor Economics (IZA).
    6. Anthony Edo & Nicolas Jacquemet & Constantine Yannelis, 2019. "Language skills and homophilous hiring discrimination: Evidence from gender and racially differentiated applications," Review of Economics of the Household, Springer, vol. 17(1), pages 349-376, March.
    7. Kevin Lang & Ariella Kahn-Lang Spitzer, 2020. "Race Discrimination: An Economic Perspective," Journal of Economic Perspectives, American Economic Association, vol. 34(2), pages 68-89, Spring.
    8. Yang, Hui & Chen, Jing & Chen, Xu & Chen, Bintong, 2017. "The impact of customer returns in a supply chain with a common retailer," European Journal of Operational Research, Elsevier, vol. 256(1), pages 139-150.
    9. Bryson, Alex & Chevalier, Arnaud, 2015. "Is there a taste for racial discrimination amongst employers?," Labour Economics, Elsevier, vol. 34(C), pages 51-63.
    10. Vera Brenčič, 2016. "The impact of Craigslist’s entry on competing employment websites," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-15, December.
    11. Morten Størling Hedegaard & Jean-Robert Tyran, 2018. "The Price of Prejudice," American Economic Journal: Applied Economics, American Economic Association, vol. 10(1), pages 40-63, January.
    12. Claudia Keser & Maximilian Späth, 2020. "The Value of Bad Ratings: An Experiment on the Impact of Distortions in Reputation Systems," CIRANO Working Papers 2020s-22, CIRANO.
    13. Jacquemet, Nicolas & Yannelis, Constantine, 2012. "Indiscriminate discrimination: A correspondence test for ethnic homophily in the Chicago labor market," Labour Economics, Elsevier, vol. 19(6), pages 824-832.
    14. Castillo, Marco & Petrie, Ragan & Torero, Maximo & Vesterlund, Lise, 2013. "Gender differences in bargaining outcomes: A field experiment on discrimination," Journal of Public Economics, Elsevier, vol. 99(C), pages 35-48.
    15. Lingfang (Ivy) Li & Steven Tadelis & Xiaolan Zhou, 2016. "Buying Reputation as a Signal of Quality: Evidence from an Online Marketplace," NBER Working Papers 22584, National Bureau of Economic Research, Inc.
    16. Siddique, Abu & Vlassopoulos, Michael & Zenou, Yves, 2020. "Market Competition and Discrimination," IZA Discussion Papers 13269, Institute of Labor Economics (IZA).
    17. 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.
    18. Kakar, Venoo & Voelz, Joel & Wu, Julia & Franco, Julisa, 2018. "The Visible Host: Does race guide Airbnb rental rates in San Francisco?," Journal of Housing Economics, Elsevier, vol. 40(C), pages 25-40.
    19. Jin, Delong & Caliskan-Demirag, Ozgun & Chen, Frank (Youhua) & Huang, Min, 2020. "Omnichannel retailers’ return policy strategies in the presence of competition," International Journal of Production Economics, Elsevier, vol. 225(C).
    20. Joshua S. Gans & Avi Goldfarb & Mara Lederman, 2017. "Exit, Tweets, and Loyalty," Working Papers 2017-009, Human Capital and Economic Opportunity Working Group.

    More about this item

    JEL classification:

    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • 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:nbr:nberwo:25917. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: http://edirc.repec.org/data/nberrus.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.