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So, Who Likes You? Evidence from a Randomized Field Experiment

Author

Listed:
  • Ravi Bapna

    (Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455)

  • Edward McFowland

    (Harvard Business School, Harvard University, Boston, Massachusetts 02163)

  • Probal Mojumder

    (Operations Management, Quantitative Methods and Information Systems Area, Indian Institute of Management Udaipur, Balicha, Udaipur, Rajasthan 313001, India)

  • Jui Ramaprasad

    (Robert H. Smith School of Business, University of Maryland, College Park, Maryland 20742)

  • Akhmed Umyarov

    (Unaffiliated)

Abstract

With one-third of marriages in the United States beginning online, online dating platforms have become important curators of the modern social fabric. Prior work on online dating has elicited two critical frictions in the heterosexual dating market. Women, governed by age-old social norms of not making the first move, are inhibited in their interactions in that they do not initiate contact with men. On the other side, men send an abundance of messages, the majority of which do not convert to matches. A key distinguishing feature of online dating versus its traditional counterpart is the ability to leave a range of digital signals not replicable in the offline world. These digital signals can impact the nature of online dating platform outcomes. In this paper, we study the impact of a feature that reveals “ who likes you ” (WLY) on engagement, the number of matches, match efficiency, and match sorting in online dating. This feature reveals the identity of the voters who have rated the focal user with a like. To causally identify the effect of this feature, we conduct a large-scale randomized control trial in collaboration with a major North American dating platform. The treatment causes women to be more proactive, sending 7.4% more messages, which is a highly desirable market improvement given that men send double the number of messages compared with women. Further, we find that the women endowed with this feature increase their matches by 14.4%, whereas men increase their matches by 11.5%. Analyzing the moderating impact of desirability—a key aspect of the WLY feature—provides us with nuanced findings. Depending on the levels of each of the two parties’ desirability, we see evidence of sorting, encouragement, and discouragement.

Suggested Citation

  • Ravi Bapna & Edward McFowland & Probal Mojumder & Jui Ramaprasad & Akhmed Umyarov, 2023. "So, Who Likes You? Evidence from a Randomized Field Experiment," Management Science, INFORMS, vol. 69(7), pages 3939-3957, July.
    • Handle: RePEc:inm:ormnsc:v:69:y:2023:i:7:p:3939-3957
    DOI: 10.1287/mnsc.2022.4576
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    References listed on IDEAS

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    1. Gordon Burtch & Anindya Ghose & Sunil Wattal, 2016. "Secret Admirers: An Empirical Examination of Information Hiding and Contribution Dynamics in Online Crowdfunding," Information Systems Research, INFORMS, vol. 27(3), pages 478-496, September.
    2. Raymond Fisman & Sheena S. Iyengar & Emir Kamenica & Itamar Simonson, 2006. "Gender Differences in Mate Selection: Evidence From a Speed Dating Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(2), pages 673-697.
    3. David Holtz & Sinan Aral, 2020. "Limiting Bias from Test-Control Interference in Online Marketplace Experiments," Papers 2004.12162, arXiv.org.
    4. Gunter J. Hitsch & Ali Hortaçsu & Dan Ariely, 2010. "Matching and Sorting in Online Dating," American Economic Review, American Economic Association, vol. 100(1), pages 130-163, March.
    5. Chris Forman & Anindya Ghose & Batia Wiesenfeld, 2008. "Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets," Information Systems Research, INFORMS, vol. 19(3), pages 291-313, September.
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