Multi-sided platforms - A study on pricing dynamics and network effects

Abstract

This thesis studies the pricing strategies of multi-sided platforms and how their specific market characteristics affect the pricing decisions of platform operators. Multi-sided platforms have received considerable attention in economics research, and this study presents an overview of their market characteristics, pricing strategies and market outcomes under competition. I present the key findings and assess possible limitations of models derived by Armstrong (2006) and Rochet & Tirole (2006) describing two-sided markets.

To see how these models can be applied I investigate a case industry of the two-sided daily deals market, where online intermediaries collect and distribute deals between merchants and customers. My results show that when the underlying assumptions of the models are compared with what is reported by the existing research for the daily deals market, the models can only be deemed to provide insights on a general level. Most significant shortcomings are related to the assumption on customer heterogeneity and the different pricing instruments used in the daily deals market compared to the assumptions in the benchmark models. In order to fully capture the specific dynamics of the case market I discuss some major alterations that should be done to the frameworks applied, and present potential approaches to build a more accurate model to describe the case market.