Tipping Markets in Digital Age: Pre-Tipping or Post-Tipping Interventions
In class and the textbook, we learn how to find equilibria in a market with network effects. Specifically, the tipping point as equilibrium is unstable but important when firms market a new product. However, it might be more interesting to talk about the factors that determine how strong network effects are in the context of our digital age.
According to Helen Jenkins, data-enabled learning, or Big Data, allows firms to optimize the development of new and existing products, ultimately benefitting consumers and firms. Specifically, data analysis enables firms to identify design flaws in existing products and the most attractive characteristics of products and services to better identify and meet consumer needs. Big Data amplifies direct network effects in a cycle: having a successful product allows a firm to collect more data and improve its products, which brings in more users, who help the firms identify even more diverse consumer needs and become better. This cycle reminds me of the last question of HW7: when more information kicks in, the popularity distribution of products becomes more extreme. The situation is similar here but different in a way that in the question, information is provided for users while here it is also utilized by firms. This feature might even make the network effects stronger.
Although data analysis may lead to positive network effects and benefit both users and firms, the natural tendency of tipping markets to host only a few firms has led some competition authorities to be concerned by potential abuse of dominance by the suppliers, especially in the digital sector, according to Jenkins. She introduces the government’s role in tipping markets and a critical decision in the design of interventions: whether interventions should occur before or after tipping. To summarize her ideas, the concern about pre-tipping regulations is the difficulty of identifying which markets will tip. However, my intuitive concern about these interventions is whether these firms have enough incentives to abuse their market dominance, which is not addressed in Jenkins’ proposal. The example given by Jenkins can support my intuition: Robert Metcalfe—the inventor of the ethernet protocol used to access the Internet—predicted in 1995 that ‘the internet will soon go spectacularly supernova and in 1996 catastrophically collapse.’ While she uses this example to illustrate the unpredictability of a certain firm’s tipping, I may argue that predicting whether a firm would eventually abuse its dominant power is also difficult. Perhaps we should be thankful that regulators did not strangle the Internet in its infancy because they suspended its potential abuse in the future (just my intuitive ideas).
Jenkins’s points about post-tipping interventions are insightful. Post-tipping regulations for abuse–sometimes taking years to reach a conclusion–might arrive too late to appropriately remedy a competition concern because the market may have long tipped, and potential competitors may have disappeared. Unfortunately, considering the trade-off between pre-tipping and post-tipping regulation, we conclude that “it always depends.” Pre-tipping regulations to prevent potential abuse might not be legitimate enough, while post-tipping interventions might not be efficient enough. Fortunately, Jenkins mentions that competition authorities worldwide are experimenting with both types of approach, and time will tell which toolset regulation will tip towards.
Source: https://www.oxera.com/insights/agenda/articles/tipping-should-regulators-intervene-before-or-after-a-policy-dilemma/