Empirical Analysis of Referrals in Ride-Sharing

33 Pages Posted: 26 Mar 2019 Last revised: 12 Nov 2019

See all articles by Maxime Cohen

Maxime Cohen

McGill University

Carlos Fernández

New York University (NYU) - Leonard N. Stern School of Business

Anindya Ghose

New York University (NYU) - Leonard N. Stern School of Business

Date Written: March 2, 2019

Abstract

Firms often offer the option to refer friends in exchange for a reward. In this paper, we empirically address the question of how service usage---in terms of experience level, current usage intensity, and recency---affects the probability of making referrals and the quality of those referrals. We incorporate dynamic behavior in our models to analyze how past referrals affect future referrals. We partner with a ride-sharing platform, allowing us to access a large panel dataset on transactions and referral actions. We estimate econometric models that account for unobserved heterogeneity to show that the probability of making a referral increases with the experience level (captured by the number of past rides), increases with the current usage intensity (number of rides in the previous week), decreases with long inactivity periods, and decreases with past high quality referrals. We also find that referral quality---measured by the number of rides completed by the referred customer---increases with experience and decreases with past high quality referrals. Finally, we consider a prescriptive campaign in which the platform sent notifications to remind users about the referral program. Using data from a field experiment, we show that such notifications can increase referral rates by 46% and generate significant marginal revenue.

Keywords: Referrals, Ride-Sharing, Field Experiments, Online Platforms

Suggested Citation

Cohen, Maxime and Fernández, Carlos and Ghose, Anindya, Empirical Analysis of Referrals in Ride-Sharing (March 2, 2019). Available at SSRN: https://ssrn.com/abstract=3345669 or http://dx.doi.org/10.2139/ssrn.3345669

Maxime Cohen (Contact Author)

McGill University ( email )

1001 Sherbrooke St. W
Montreal, Quebec H3A 1G5
Canada

Carlos Fernández

New York University (NYU) - Leonard N. Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States

Anindya Ghose

New York University (NYU) - Leonard N. Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States

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