4 - Personal Data and Collective Value: Data-Driven Personalisation as Network Effect

Summary

Over recent years, economists, lawyers and regulators have become increasingly interested in the role played by ‘network effects’ in the digital economy: namely, the phenomenon whereby a platform becomes increasingly valuable to its users, the more users it succeeds in recruiting. Whether user-generated content on Youtube and Facebook, proprietorial messaging services such as Whatsapp, or two-sided markets such as Uber and Airbnb, it is now widely recognised that many of today’s most successful technology businesses enjoy a dominance based upon achieving a critical mass of users, which makes it near-impossible for less well-used platforms to compete. What is less widely recognised is that data-driven personalisation operates in a comparable (albeit not identical) manner: as the volume of users increases, personalisation becomes ever more sophisticated, generating a ‘second-order’ network effect that can also have significant implications for the viability of competition. This paper unpacks the distinction between first-order and second-order network effects, showing how both can create significant barriers to competition. It analyses what second-order network effects imply for how governments can and should regulate data-driven personalisation, and how states might help their citizens to regain control over the value that they create.