Complexity and obfuscation in evolving platform pricing

Abstract

Two-sided platforms include some of the largest and fastest-growing businesses of the past decade. They are composed of three parts: two distinct groups of end-users and a platform. Two-sided platforms face unique challenges such as design, pricing, governance rules etc. The pricing decision specifically has been the subject of rigorous research. As the value that each group derives from using the platform depends on the size of the other side of the market, the platform's pricing strategies of the two groups are closely linked. A platform pricing strategy includes decisions about which side of the platform to charge, how much to charge them and an overall approach to attract and benefit both sides of the platform. Though the study of platform strategies has been quite popular among many economists, they have focused on analyzing the strategies from a static perspective. Because platforms have evolved their pricing strategies over time to be competitive in the market and have faced challenges, the process deserves attention. This thesis therefore analyzes the evolution of pricing strategies of platforms such as eBay (sellers and buyers) and Uber (riders and drivers) and the challenges they overcame to stay ahead in the market. We study that eBay initially used a complex pricing strategy but simplified it to compete in the market with Amazon and other e-commerce firms. Uber, in contrast, began with a simple "taxi-meter" pricing but changed their pricing strategy to account for the multiple variables such as demand, supply, location etc. The study concludes that to stay relevant in the market and to be successful, platforms need to evolve their pricing strategy over time depending on various market conditions. Though there is not one fixed pattern of how platforms evolve their pricing, their strategies consider simplicity, data availability and transparency while making pricing decisions. Future platforms can use these learnings while designing their pricing strategies.