Network effects in two-sided markets: why a 50/50 user split is not necessarily revenue optimal

Sebastian Voigt,Oliver Hinz

doi:10.1007/s40685-015-0018-z

Sebastian Voigt, Oliver Hinz

Open Access

https://doi.org/10.1007/s40685-015-0018-z

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Abstract

AbstractOur study applies empirical scrutiny to the network effects of a leading European online dating platform. While one might expect equal gender representation on such a platform to yield the best user experience and the highest revenue per user, our analysis shows that the platform requires only 36.2 % of its user base to be female to maximize revenue, primarily because women exert stronger positive cross-side network effects on men than vice versa; this optimum results in 17.2 % higher sales than a 50/50 split. Intermediaries of two-sided markets can use our model to improve user acquisition strategies.

Highlights

In two-sided markets, an intermediary provides a platform enabling two different user groups to interact, for instance to make a transaction to satisfy their interdependent demands (Bakos and Katsamakas 2008; Ellison and Ellison 2005; Roch1et and Tirole 2003, 2006)
While one might expect equal gender representation on such a platform to yield the best user experience and the highest revenue per user, our analysis shows that the platform requires only 36.2 % of its user base to be female to maximize revenue, primarily because women exert stronger positive cross-side network effects on men than vice versa; this optimum results in 17.2 % higher sales than a 50/50 split
We observed that both user groups exert positive cross-side network effects (CNEs) with regard to revenue and user enrollment of the other group; the positive CNEs women exert on revenue generation per man are stronger than vice versa

Summary

Introduction

In two-sided markets, an intermediary provides a platform enabling two different user groups to interact, for instance to make a transaction to satisfy their interdependent demands (Bakos and Katsamakas 2008; Ellison and Ellison 2005; Roch1et and Tirole 2003, 2006). EBay, for example, brings together sellers and prospective buyers of different kinds of goods, Google advertisers and web users, and prosper lenders and borrowers of private loans. Previous research on two-sided markets indicates that the two user groups exhibit different kinds of network effects (Katz and Shapiro 1985; Liebowitz and Margolis 1994). Users may derive positive cross-side network effects (CNEs) from the participation of members on the other side of the market, which means the larger the installed user base on one side of the platform, the more attractive the service for the opposite side’s users (Armstrong 2006; Li et al 2010; Tucker and Zhang 2010). A new eBay seller can have a negative effect on other sellers because he or she increases competition between sellers and may snatch away potential buyers (Kraemer et al 2012; Li et al 2010)

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