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

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.