Network Effects and Valuation

Abstract: This study examines the association between revenue and user base for companies who operate a platform-mediated business model and benefit from network effects. More specifically, the study incorporates both an exponential and linear function in order to see which one most accurately explains the association. Previous research has theorized the notion of an exponential association between revenue and user base, as the number of connections increases at an exponential rate when a new user joins a platform. Furthermore, as previous research points toward a different return on invested capital across industries, an industry variable will be incorporated. Therefore, the study aims to investigate the theoretical aspects of network effects and Metcalfe, Reed and Odlyzko’s law in order to see how these theoretical viewpoints creates the notion of an exponential association between revenue and user base. Moreover, the study aims to test the association across different industries. By incorporating data on 85 companies into both a linear and exponential regression, two findings have been observed. Firstly, the dataset cannot determine whether an exponential relationship more accurately explains the association between revenue and user base compared to a linear one. This finding therefore states the contrary to existing literature as an exponential association cannot be determined. Secondly, industry does play an important role when studying the association between revenue and user base. This finding shows that some industries are more efficient at extrapolating revenue from its user base.