Estimating the Cross-side Network Effect for Two-sided Platforms - Cases Apple iOS and Wikipedia

Kimmo Karhu*, Jani-Pekka Jokinen

*Corresponding author for this work

Research output: Contribution to conferenceAbstractScientificpeer-review

Abstract

The rise of the platform economy has completely changed the growth dynamics for businesses, such as Apple iOS and Amazon.com, as well as for nonprofits, such as Wikipedia and Open Street Maps. The exponential growth of these platforms stem from the same-side and cross-side network effects, i.e., feedback loops, within and between the platform sides. In this paper, we set out to develop a generic system dynamic model for two-sided platforms. We evaluate our model with historical data from two distinct types of platforms—Apple iOS and Wikipedia—and estimate not only the overall strength of the cross-side network effect in both directions but also its dynamic behavior. We compare these results for the two sides and between the platforms. We find that the cross-side effect is strong in both platforms for both directions. Along the existing literature, for Apple iOS, we also find that the effect is longer lasting towards the producer side. Our contribution is three-fold. We present a generic system dynamic model for modeling two-sided platforms, suggest an approach for estimating the growth rates and dynamic behavior of the cross-side network effect, and offer a comparison of platforms from two distinct domains.
Original languageEnglish
Publication statusPublished - Jul 2022
MoE publication typeNot Eligible
EventInternational Conference of the System Dynamics Society - Frankfurt, Germany
Duration: 18 Jul 202222 Jul 2022

Conference

ConferenceInternational Conference of the System Dynamics Society
Country/TerritoryGermany
CityFrankfurt
Period18/07/202222/07/2022

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